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CN113354004B - Sewage treatment method and system based on Internet and big data - Google Patents

Sewage treatment method and system based on Internet and big data Download PDF

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CN113354004B
CN113354004B CN202110646039.0A CN202110646039A CN113354004B CN 113354004 B CN113354004 B CN 113354004B CN 202110646039 A CN202110646039 A CN 202110646039A CN 113354004 B CN113354004 B CN 113354004B
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sewage
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CN113354004A (en
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熊枝光
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United Taize Environmental Technology Development Co ltd
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United Taize Environmental Technology Development Co ltd
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    • C—CHEMISTRY; METALLURGY
    • C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F1/00—Treatment of water, waste water, or sewage
    • C02F1/008—Control or steering systems not provided for elsewhere in subclass C02F

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Abstract

The application relates to a sewage treatment method and system based on the Internet and big data, which comprises the steps of obtaining a target area to be treated selected according to a specific proportion in a preset original area to be treated, respectively obtaining sewage treatment effect data corresponding to a first sewage area to be optimized, a sewage optimization advanced area and a second sewage area to be optimized according to an area obtaining and completing instruction based on a big data technology, performing data optimization treatment on the first data to be optimized and the second data to be optimized according to reference type data to be optimized, and generating a data optimization report to be stored based on the Internet technology. According to the method, on one hand, the first data to be optimized and the second data to be optimized are optimized according to the data of the sewage optimization advanced area, so that the optimization of the sewage treatment in a large area is realized, on the other hand, the high-efficiency analysis and storage of the data are realized based on the large data and the Internet technology, and the efficiency and the high efficiency of the sewage data treatment are improved.

Description

Sewage treatment method and system based on Internet and big data
Technical Field
The application relates to the technical field of sewage treatment, in particular to a sewage treatment method and system based on the Internet and big data.
Background
Sewage treatment is a process for purifying sewage to meet the water quality requirement of discharging the sewage into a certain water body or reusing the sewage. Sewage treatment is widely applied to various fields such as building, agriculture, traffic, energy, petrifaction, environmental protection, urban landscape, medical treatment, catering and the like, and is increasingly used in daily life of common people. With the development of big data and internet technology, sewage treatment is gradually combined with internet and big data, for example, an integrated distributed rural sewage treatment station intelligent control system is disclosed in an invention patent document with the application number of CN201910709092.3, a data acquisition module is used for acquiring operation state data of sewage treatment equipment, a video monitoring module is used for monitoring the sewage treatment process of the sewage treatment station in real time, a water quality monitoring module is used for detecting sewage quality information in the sewage treatment equipment and transmitting the information to an internet and cloud data platform, and the internet and cloud data platform is used for arranging and managing the data and uploading the data to a remote control platform and a mobile terminal.
Although the relevant effect of relevant sewage treatment can be realized, the problem that the sewage treatment efficiency is not efficient and the sewage treatment effect is unbalanced is caused and the development of an area is influenced by the condition that the sewage treatment effect of a local area is better and the sewage treatment effect of other areas is poorer aiming at the unbalanced condition of the sewage treatment in a large area at present.
Disclosure of Invention
In view of the above, it is necessary to provide a sewage treatment method and system based on internet and big data, which can improve the data processing efficiency.
The technical scheme of the invention is as follows:
an internet and big data based sewage treatment method, the method comprising:
acquiring a target area to be processed selected according to a specific proportion from a preset original area to be processed, and generating an area acquisition completion instruction after the target area to be processed is acquired, wherein the target area to be processed comprises a first area to be optimized for sewage, a high-grade area for sewage optimization and a second area to be optimized for sewage, and the distance interval between every two areas of the first area to be optimized for sewage, the high-grade area for sewage optimization and the second area to be optimized for sewage is less than or equal to a preset standard interval distance; respectively acquiring sewage treatment effect data corresponding to the first sewage to-be-optimized area, the sewage optimization advanced area and the second sewage to-be-optimized area according to the area acquisition completion instruction based on a big data technology, wherein the sewage treatment effect data of the first sewage to-be-optimized area is first to-be-optimized data, the sewage treatment effect data of the sewage optimization advanced area is reference type to-be-optimized data, and the sewage treatment effect data of the second sewage to-be-optimized area is second to-be-optimized data; and performing data optimization processing on the first data to be optimized and the second data to be optimized according to the reference data to be optimized, and generating a data optimization report to be stored based on the Internet technology.
Specifically, a target area to be processed selected according to a specific proportion in a preset original area to be processed is obtained, and an area obtaining completion instruction is generated after the target area to be processed is obtained, wherein the target area to be processed comprises a first area to be optimized for sewage, a high-grade area for sewage optimization and a second area to be optimized for sewage, and the distance interval between every two of the first area to be optimized for sewage, the high-grade area for sewage optimization and the second area to be optimized for sewage is less than or equal to a preset standard interval distance; the method specifically comprises the following steps: acquiring a high-level region setting triggering instruction for triggering high-level region selection in an original region to be processed, acquiring an initial high-level region based on the high-level region setting triggering instruction, and simultaneously judging whether the initial high-level region meets a preset high-level region evaluation standard; if the initial high-grade area meets the preset high-grade area evaluation standard, extracting a target area meeting the high-grade area evaluation standard in the initial high-grade area, setting the target area as a sewage optimization high-grade area, and simultaneously acquiring basic environment data of the high-grade area evaluation standard; acquiring a large-scale sewage treatment area which is in the same sewage treatment area as the sewage optimization advanced area in the original area to be treated based on the sewage optimization advanced area; screening a plurality of original sewage to-be-optimized areas in a circular area which is formed by taking the sewage optimization high-grade area as a core and outwards extending by taking a specific standard spacing distance as a radius according to the sewage treatment flow direction in the large-range sewage treatment area; respectively obtaining current actual environment data of each original sewage area to be optimized, comparing the current actual environment data with the basic environment data in similarity, and screening out the maximum value of the similarity numerical value and the second maximum value of the similarity numerical value; and setting the original sewage to-be-optimized region corresponding to the maximum value of the similarity value and the second maximum value of the similarity value as the first sewage to-be-optimized region and the second sewage to-be-optimized region.
Specifically, data optimization processing is carried out on the first data to be optimized and the second data to be optimized according to the reference data to be optimized, and a data optimization report is generated and stored based on the internet technology; the method specifically comprises the following steps:
acquiring a first incidence relation weighing value between the first sewage to-be-optimized region and the sewage optimization advanced region based on the reference type data to be optimized; acquiring a second association relation weighing value between the second sewage to-be-optimized region and the sewage optimization high-level region based on the reference type data to be optimized; acquiring a first additional influence value of the sewage optimization advanced region on the first sewage to-be-optimized region according to the first incidence relation weighing value; acquiring a second additional influence value of the sewage optimization advanced region on the first sewage to-be-optimized region according to the second incidence relation weighing value; generating a comprehensive additional influence value according to the first additional influence value and the second additional influence value, and extracting optimization processing data for performing data optimization on the first data to be optimized and the second data to be optimized according to the reference data to be optimized; and filtering the comprehensive additional influence value from the optimization processing data, generating upgrade optimization processing data, performing data optimization processing on the first data to be optimized and the second data to be optimized based on the upgrade optimization processing data, and generating a data optimization report to be stored based on the internet technology.
Specifically, acquiring a high-level region setting trigger instruction for triggering high-level region selection in an original region to be processed, acquiring an initial high-level region based on the high-level region setting trigger instruction, and simultaneously judging whether the initial high-level region meets a preset high-level region evaluation standard; the method specifically comprises the following steps:
acquiring a high-grade area setting triggering instruction for triggering high-grade area selection in an original area to be processed, acquiring an initial high-grade area based on the high-grade area setting triggering instruction, and calling a sewage environment processing auditing standard of an area where the initial high-grade area is located in real time; processing and judging the initial high-grade area based on the called sewage environment processing auditing standard, and generating an initial judging result; judging whether the initial judgment result meets a preset qualified judgment result value or not based on the generated initial judgment result; if the initial judgment result does not meet the preset qualified judgment result value, generating a reexamination judgment instruction, and searching objective natural environment influence data in a specific time period based on the reexamination judgment instruction; performing result correction processing on the initial judgment result based on the objective natural environment influence data, generating a reexamination judgment result, and meanwhile judging whether the reexamination judgment result meets a preset qualified judgment result value; if the re-review judgment result meets a preset qualified judgment result value, judging that the initial high-level region meets a preset high-level region evaluation standard; and if the re-examination and judgment result does not meet the preset qualified judgment result value, judging that the initial high-grade area does not meet the preset high-grade area evaluation standard.
Specifically, acquiring a high-level area setting triggering instruction for triggering high-level area selection in an original area to be processed, acquiring an initial high-level area based on the high-level area setting triggering instruction, and calling a sewage environment processing auditing standard of an area where the initial high-level area is located in real time; and then also comprises the following steps:
acquiring auxiliary judgment information of sewage treatment; extracting auxiliary judgment requirement data in the auxiliary sewage treatment judgment information according to a preset keyword extraction model based on the auxiliary sewage treatment judgment information, and generating previous standard judgment requirement data based on the sewage environment treatment auditing standard; performing data feature iteration on the previous standard evaluation requirement data based on the auxiliary evaluation requirement data, and generating update requirement data between the auxiliary evaluation requirement data and the previous standard evaluation requirement data; and performing incremental learning on the sewage environment treatment auditing standard according to the updating requirement data, and generating an updated sewage treatment auditing standard.
Specifically, an internet and big data based sewage treatment system, the system comprising:
the system comprises a processing area module, a data processing module and a data processing module, wherein the processing area module is used for acquiring a target area to be processed selected according to a specific proportion in a preset original area to be processed and generating an area acquisition completion instruction after the target area to be processed is acquired, the target area to be processed comprises a first sewage area to be optimized, a sewage optimization advanced area and a second sewage area to be optimized, and the distance interval between every two of the first sewage area to be optimized, the sewage optimization advanced area and the second sewage area to be optimized is smaller than or equal to a preset standard interval distance;
the data technology module is used for respectively acquiring sewage treatment effect data corresponding to the first sewage to-be-optimized area, the sewage optimization advanced area and the second sewage to-be-optimized area according to the area acquisition completion instruction based on a big data technology, wherein the sewage treatment effect data of the first sewage to-be-optimized area is first data to be optimized, the sewage treatment effect data of the sewage optimization advanced area is reference data to be optimized, and the sewage treatment effect data of the second sewage to-be-optimized area is second data to be optimized;
and the optimization processing module is used for performing data optimization processing on the first data to be optimized and the second data to be optimized according to the reference data to be optimized and generating a data optimization report to be stored based on the Internet technology.
Specifically, the processing region module is further configured to: acquiring a high-level region setting triggering instruction for triggering high-level region selection in an original region to be processed, acquiring an initial high-level region based on the high-level region setting triggering instruction, and simultaneously judging whether the initial high-level region meets a preset high-level region evaluation standard; if the initial advanced area meets the preset advanced area evaluation standard, extracting a target area meeting the advanced area evaluation standard in the initial advanced area, setting the target area as a sewage optimization advanced area, and acquiring basic environment data of the advanced area evaluation standard; acquiring a large-scale sewage treatment area which is in the same sewage treatment area as the sewage optimization advanced area in the original area to be treated based on the sewage optimization advanced area; screening a plurality of original sewage areas to be optimized in a circular area formed by outwards extending by taking the sewage optimization advanced area as a core and taking a specific standard spacing distance as a radius according to the sewage treatment flow direction in the large-range sewage treatment area; respectively obtaining current actual environment data of each original sewage area to be optimized, comparing the current actual environment data with the basic environment data in similarity, and screening out the maximum value of the similarity numerical value and the second maximum value of the similarity numerical value; and setting the original sewage to-be-optimized region corresponding to the maximum value of the similarity value and the second maximum value of the similarity value as the first sewage to-be-optimized region and the second sewage to-be-optimized region.
Specifically, the optimization processing module is further configured to: acquiring a first incidence relation weighing value between the first sewage to-be-optimized region and the sewage optimization advanced region based on the reference type data to be optimized; acquiring a second incidence relation weighing value between the second sewage to-be-optimized region and the sewage optimization advanced region based on the reference type data to be optimized; acquiring a first additional influence value of the sewage optimization advanced region on the first sewage to-be-optimized region according to the first association relation weighing value; acquiring a second additional influence value of the sewage optimization advanced region on the first sewage to-be-optimized region according to the second incidence relation weighing value; generating a comprehensive additional influence value according to the first additional influence value and the second additional influence value, and extracting optimization processing data for performing data optimization on the first data to be optimized and the second data to be optimized according to the reference data to be optimized; filtering the comprehensive additional influence value from the optimized processing data, generating upgraded optimized processing data, performing data optimization processing on the first to-be-optimized data and the second to-be-optimized data based on the upgraded optimized processing data, and generating a data optimization report to be stored based on the internet technology; acquiring a high-grade area setting triggering instruction for triggering high-grade area selection in an original area to be processed, acquiring an initial high-grade area based on the high-grade area setting triggering instruction, and calling a sewage environment processing auditing standard of an area where the initial high-grade area is located in real time; processing and judging the initial high-grade area based on the called sewage environment processing auditing standard, and generating an initial judging result; judging whether the initial judgment result meets a preset qualified judgment result value or not based on the generated initial judgment result; if the initial judgment result does not meet the preset qualified judgment result value, generating a reexamination judgment instruction, and searching objective natural environment influence data in a specific time period based on the reexamination judgment instruction; performing result correction processing on the initial judgment result based on the objective natural environment influence data, generating a reexamination judgment result, and meanwhile judging whether the reexamination judgment result meets a preset qualified judgment result value; if the re-review judgment result is judged to meet a preset qualified judgment result value, judging that the initial high-level region meets a preset high-level region evaluation standard; and if the re-examination and judgment result does not meet the preset qualified judgment result value, judging that the initial high-grade area does not meet the preset high-grade area evaluation standard.
The optimization processing module is further configured to: acquiring auxiliary judgment information of sewage treatment; extracting auxiliary judgment requirement data in the auxiliary sewage treatment judgment information according to a preset keyword extraction model based on the auxiliary sewage treatment judgment information, and generating previous standard judgment requirement data based on the sewage environment treatment auditing standard; performing data feature iteration on the previous standard evaluation requirement data based on the auxiliary evaluation requirement data, and generating update requirement data between the auxiliary evaluation requirement data and the previous standard evaluation requirement data; and performing incremental learning on the sewage environment treatment auditing standard according to the updating requirement data, and generating an updated sewage treatment auditing standard.
Specifically, the computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the sewage treatment method based on the internet and the big data when executing the computer program.
Specifically, a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the steps of the above-described internet-and big-data-based sewage treatment method.
The invention has the following technical effects:
according to the sewage treatment method and system based on the Internet and the big data, a target area to be treated selected according to a specific proportion in a preset original area to be treated is obtained in sequence, and an area obtaining completion instruction is generated after the target area to be treated is obtained, wherein the target area to be treated comprises a first sewage area to be optimized, a sewage optimization advanced area and a second sewage area to be optimized, and the distance interval between every two of the first sewage area to be optimized, the sewage optimization advanced area and the second sewage area to be optimized is smaller than or equal to a preset standard interval distance; respectively acquiring sewage treatment effect data corresponding to the first sewage to-be-optimized area, the sewage optimization advanced area and the second sewage to-be-optimized area according to the area acquisition completion instruction based on a big data technology, wherein the sewage treatment effect data of the first sewage to-be-optimized area is first data to be optimized, the sewage treatment effect data of the sewage optimization advanced area is reference data to be optimized, and the sewage treatment effect data of the second sewage to-be-optimized area is second data to be optimized; and performing data optimization processing on the first data to be optimized and the second data to be optimized according to the reference data to be optimized, and generating a data optimization report for storage based on the internet technology, so that on one hand, the sewage treatment data of an area in which superior sewage treatment is realized in a large area is optimized according to the sewage treatment data of the area in which superior sewage treatment is realized, and on the other hand, other areas in which sewage treatment is to be optimized in the large area are optimized, namely, the first data to be optimized and the second data to be optimized are optimized according to the data of a high-level area in the sewage treatment, so that the first data to be optimized and the second data to be optimized tend to the reference data to be optimized, and further, the simultaneous optimization of the sewage treatment in the large area is realized, and on the other hand, the efficient analysis and storage of the data are realized based on the large data and the internet technology, and further, and the efficiency of the sewage data treatment are improved.
Drawings
FIG. 1 is a schematic flow diagram of an Internet and big data based wastewater treatment process according to an embodiment;
FIG. 2 is a block diagram of an embodiment of an Internet and big data based sewage treatment system;
FIG. 3 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of and not restrictive on the broad application.
In one embodiment, the internet and big data based sewage treatment method is further based on an application scenario, the scenario includes a terminal, the terminal acquires a target area to be treated selected according to a specific proportion from preset original areas to be treated, and generates an area acquisition completion instruction after the target area to be treated is acquired, wherein the target area to be treated includes a first sewage area to be optimized, a sewage optimization advanced area and a second sewage area to be optimized, and a distance interval between every two of the first sewage area to be optimized, the sewage optimization advanced area and the second sewage area to be optimized is less than or equal to a preset standard interval distance; then, the terminal respectively acquires sewage treatment effect data corresponding to the first sewage to-be-optimized area, the sewage optimization advanced area and the second sewage to-be-optimized area according to the area acquisition completion instruction based on a big data technology, wherein the sewage treatment effect data of the first sewage to-be-optimized area is first data to be optimized, the sewage treatment effect data of the sewage optimization advanced area is reference type data to be optimized, and the sewage treatment effect data of the second sewage to-be-optimized area is second data to be optimized; and then the terminal performs data optimization processing on the first data to be optimized and the second data to be optimized according to the reference data to be optimized, and generates a data optimization report to be stored based on the Internet technology.
In one embodiment, as shown in fig. 1, there is provided an internet and big data based sewage treatment method, the method comprising:
step S100: acquiring a target area to be processed selected according to a specific proportion in a preset original area to be processed, and generating an area acquisition completion instruction after the target area to be processed is acquired, wherein the target area to be processed comprises a first area to be optimized for sewage, a high-grade area for sewage optimization and a second area to be optimized for sewage, and the distance interval between every two of the first area to be optimized for sewage, the high-grade area for sewage optimization and the second area to be optimized for sewage is less than or equal to a preset standard interval distance;
further, in this step, the original region to be processed needs to be acquired first. The original area to be processed is a large environmental area where the user is located, such as an entire ballast area. The target area to be treated is a local area in the original area to be treated, and the target area to be treated is an area participating in sewage treatment.
And the original region to be processed is selected in advance, for example, the Shenzhen south mountain region is selected as the original region to be processed. And modeling the Shenzhen nan mountainous region through big data and an internet technology, and generating a region map of the Shenzhen nan mountainous region, wherein the region map comprises the geographical identification and the related building distribution of the Shenzhen nan mountainous region.
After the original area to be treated is selected, a part of the area which is subjected to sewage treatment, namely the target area to be treated is selected from the original area to be treated. Specifically, in this step, the modeled area map may be displayed on a data terminal, and the user may select the target area to be processed on the data terminal.
The selection of the target area to be treated needs to ensure that the target area to be treated comprises a first sewage area to be optimized, a sewage optimization advanced area and a second sewage area to be optimized, and simultaneously ensures that the distance interval between every two of the first sewage area to be optimized, the sewage optimization advanced area and the second sewage area to be optimized is less than or equal to a preset standard interval distance.
Furthermore, the sewage treatment effect of the sewage optimization advanced area is higher than that of the first sewage to-be-optimized area and the second sewage to-be-optimized area.
Step 200: respectively acquiring sewage treatment effect data corresponding to the first sewage to-be-optimized area, the sewage optimization advanced area and the second sewage to-be-optimized area according to the area acquisition completion instruction based on a big data technology, wherein the sewage treatment effect data of the first sewage to-be-optimized area is first to-be-optimized data, the sewage treatment effect data of the sewage optimization advanced area is reference type to-be-optimized data, and the sewage treatment effect data of the second sewage to-be-optimized area is second to-be-optimized data;
in this step, the first data to be optimized, the reference data to be optimized, and the second data to be optimized are data stored in the sewage treatment process of the first sewage area to be optimized, the sewage optimization advanced area, and the second sewage area to be optimized, such as sewage treatment process data, sewage treatment solution problem data, sewage treatment effect data, and sewage treatment current situation data.
Furthermore, in the process of acquiring the first data to be optimized, the reference data to be optimized and the second data to be optimized, a big data technology is applied, for example, the data in the sewage treatment process is efficiently collected through the big data technology.
In this step, the first data to be optimized, the reference data to be optimized and the second data to be optimized are obtained respectively, so that the sewage treatment of the same batch in the same large area is realized subsequently.
Step S300: and performing data optimization processing on the first data to be optimized and the second data to be optimized according to the reference data to be optimized, and generating a data optimization report to be stored based on the Internet technology.
Further, the reference-type data to be optimized contains data capable of achieving a high sewage treatment effect, so that the data contained in the reference-type data to be optimized can be used as reference data, and the first data to be optimized and the second data to be optimized are subjected to data optimization according to the reference-type data to be optimized, so that a scheme that the sewage treatment effect existing in the data optimization of the first data to be optimized and the second data to be optimized is not ideal is improved.
And further, after the data optimization report is generated and stored based on the internet technology, an internet display interface is also generated and used for displaying the data optimization report.
In one embodiment, step S100: acquiring a target area to be processed selected according to a specific proportion in a preset original area to be processed, and generating an area acquisition completion instruction after the target area to be processed is acquired, wherein the target area to be processed comprises a first area to be optimized for sewage, a high-grade area for sewage optimization and a second area to be optimized for sewage, and the distance interval between every two of the first area to be optimized for sewage, the high-grade area for sewage optimization and the second area to be optimized for sewage is less than or equal to a preset standard interval distance; the method specifically comprises the following steps:
step S110: acquiring a high-level region setting triggering instruction for triggering high-level region selection in an original region to be processed, acquiring an initial high-level region based on the high-level region setting triggering instruction, and simultaneously judging whether the initial high-level region meets a preset high-level region evaluation standard;
step S120: if the initial advanced area meets the preset advanced area evaluation standard, extracting a target area meeting the advanced area evaluation standard in the initial advanced area, setting the target area as a sewage optimization advanced area, and acquiring basic environment data of the advanced area evaluation standard;
further, in this step, an initial high-level region is obtained, which is obtained after the initial high-level region is simply determined for the first time, and in order to ensure the accuracy of the obtained initial high-level region, a target region that meets the high-level region estimation standard in the initial high-level region is extracted after the initial high-level region is determined to meet a preset high-level region estimation standard, and the target region is set as a sewage optimization high-level region.
Further, basic environment data of the advanced area evaluation standard is obtained at the same time, and the basic environment data is basic environment data corresponding to the sewage optimization advanced area, such as greening data, building area and high-pollution enterprise distribution data.
Step S130: acquiring a large-scale sewage treatment area which is in the same sewage treatment area as the sewage optimization advanced area in the original area to be treated based on the sewage optimization advanced area;
step S140: screening a plurality of original sewage areas to be optimized in a circular area formed by outwards extending by taking the sewage optimization advanced area as a core and taking a specific standard spacing distance as a radius according to the sewage treatment flow direction in the large-range sewage treatment area;
step S150: respectively obtaining current actual environment data of each original sewage area to be optimized, comparing the current actual environment data with the basic environment data in similarity, and screening out the maximum value of the similarity numerical value and the second maximum value of the similarity numerical value;
step S160: and setting the original sewage to-be-optimized region corresponding to the maximum value of the similarity value and the second maximum value of the similarity value as the first sewage to-be-optimized region and the second sewage to-be-optimized region.
Further, in order to ensure that the data of the sewage optimization advanced area can provide reference for other areas, a large-scale sewage treatment area in the same sewage treatment area as the sewage optimization advanced area in the original area to be treated is firstly arranged. Meanwhile, in order to ensure the accuracy and the referential property of the selected area, the area to be optimized is selected in a circular area which is formed by taking the sewage optimization high-grade area as a core and taking a specific standard spacing distance as a radius and extending outwards, namely a plurality of original sewage areas to be optimized are selected. Further, in order to ensure that the selected area is more accurate, the second screening is performed, that is, the current actual environment data is compared with the basic environment data in similarity, and the maximum value of the similarity value and the second maximum value of the similarity value are screened, that is, the original sewage to be optimized area with the highest similarity and the second highest similarity is set as the first sewage to be optimized area and the second sewage to be optimized area, so that the basic environment of the selected area to be optimized is ensured to be most similar to the environment of the area corresponding to the reference type data to be optimized as much as possible, and further, the efficient treatment of the sewage is realized.
In one embodiment, step S300: performing data optimization processing on the first data to be optimized and the second data to be optimized according to the reference data to be optimized, and generating a data optimization report to be stored based on the Internet technology; the method specifically comprises the following steps:
step S310: acquiring a first incidence relation weighing value between the first sewage to-be-optimized region and the sewage optimization advanced region based on the reference type data to be optimized;
step S320: acquiring a second incidence relation weighing value between the second sewage to-be-optimized region and the sewage optimization advanced region based on the reference type data to be optimized;
step S330: acquiring a first additional influence value of the sewage optimization advanced region on the first sewage to-be-optimized region according to the first incidence relation weighing value;
step S340: acquiring a second additional influence value of the sewage optimization advanced region on the first sewage to-be-optimized region according to the second incidence relation weighing value;
step S350: generating a comprehensive additional influence value according to the first additional influence value and the second additional influence value, and extracting optimization processing data for performing data optimization on the first data to be optimized and the second data to be optimized according to the reference data to be optimized;
further, in order to ensure the high efficiency of sewage treatment, a first association relation metric value and a second association relation metric value are obtained, and the first association relation metric value and the second association relation metric value respectively represent close relation values of association relations among the first sewage to-be-optimized area, the second sewage to-be-optimized area and the sewage optimization advanced area.
Step S360: and filtering the comprehensive additional influence value from the optimization processing data, generating upgrade optimization processing data, performing data optimization processing on the first data to be optimized and the second data to be optimized based on the upgrade optimization processing data, and generating a data optimization report to be stored based on the internet technology.
Then, generating the first additional influence value and the second additional influence value, wherein the first additional influence value and the second additional influence value are respectively influence parameters caused by differences between the advanced sewage optimization region and the first sewage to-be-optimized region and the second sewage to-be-optimized region, so that by extracting optimization processing data for performing data processing on the first data to-be-optimized data and the second data to-be-optimized data according to the reference data to be optimized, and filtering the comprehensive additional influence value, low efficiency of sewage treatment caused by mutual influence generated by the relationship between the regions is filtered out, thereby generating upgraded optimization processing data, performing data optimization processing on the first data to-be-optimized data and the second data to-be-optimized data based on the upgraded optimization processing data, and generating a data optimization report to be stored based on the internet technology, thereby realizing efficient sewage treatment based on the internet.
In one embodiment, step S110: acquiring a high-level region setting triggering instruction for triggering high-level region selection in an original region to be processed, acquiring an initial high-level region based on the high-level region setting triggering instruction, and simultaneously judging whether the initial high-level region meets a preset high-level region evaluation standard; the method specifically comprises the following steps:
step S410: acquiring a high-grade area setting triggering instruction for triggering high-grade area selection in an original area to be processed, acquiring an initial high-grade area based on the high-grade area setting triggering instruction, and calling a sewage environment processing auditing standard of an area where the initial high-grade area is located in real time;
step S420: processing and judging the initial high-grade area based on the called sewage environment processing auditing standard, and generating an initial judging result;
step S430: judging whether the initial judgment result meets a preset qualified judgment result value or not based on the generated initial judgment result;
step S440: if the initial judgment result does not meet the preset qualified judgment result value, generating a reexamination judgment instruction, and searching objective natural environment influence data in a specific time period based on the reexamination judgment instruction;
step S450: performing result correction processing on the initial judgment result based on the objective natural environment influence data, generating a reexamination judgment result, and meanwhile judging whether the reexamination judgment result meets a preset qualified judgment result value;
step S460: if the re-review judgment result meets a preset qualified judgment result value, judging that the initial high-level region meets a preset high-level region evaluation standard; and if the re-examination and judgment result does not meet the preset qualified judgment result value, judging that the initial high-grade area does not meet the preset high-grade area evaluation standard.
Further, the sewage environment treatment auditing standard is a standard for sewage treatment level determination made by related functional departments. In order to ensure the accuracy of the sewage treatment level, whether the initial judgment result meets a preset qualified judgment result value is judged by generating the initial judgment result, and when the initial judgment result does not meet the preset qualified judgment result value, a conclusion is not directly determined, but the result passes through the review again, namely objective natural environment influence data in a specific time period is searched based on the review judgment instruction.
Further, the objective natural environment influence data is an unchangeable natural event or an irreversible event, such as drought and flood disasters, occurring within a specific time period. In order to screen out misjudgment caused by such conditions, the initial judgment result is subjected to result correction processing based on the objective natural environment influence data to generate a reexamination judgment result, and whether the reexamination judgment result meets a preset qualified judgment result value is judged at the same time, so that if the reexamination judgment result meets the preset qualified judgment result value, the initial high-grade region is judged to meet a preset high-grade region evaluation standard; and if the re-review result does not meet the preset qualified result value, judging that the initial high-level region does not meet the preset high-level region evaluation standard.
In one embodiment, step S410: acquiring a high-grade area setting trigger instruction for triggering high-grade area selection in an original area to be processed, acquiring an initial high-grade area based on the high-grade area setting trigger instruction, and calling a sewage environment processing audit standard of an area where the initial high-grade area is located in real time; and then also comprises the following steps:
step S411: acquiring auxiliary judgment information of sewage treatment;
step S412: extracting auxiliary judgment requirement data in the auxiliary sewage treatment judgment information according to a preset keyword extraction model based on the auxiliary sewage treatment judgment information, and generating previous standard judgment requirement data based on the sewage environment treatment auditing standard;
step S413: performing data characteristic iteration on the previous standard evaluation requirement data based on the auxiliary evaluation requirement data, and generating update requirement data between the auxiliary evaluation requirement data and the previous standard evaluation requirement data;
step S414: and performing incremental learning on the sewage environment treatment auditing standard according to the updating requirement data, and generating an updated sewage treatment auditing standard.
Further, the auxiliary sewage treatment evaluation information is sewage treatment auxiliary evaluation information which is provided by a relevant functional unit after a sewage environment treatment audit standard is provided, and carefully commented on the sewage environment treatment audit standard, and the sewage environment treatment audit standard needs to be updated because the time for providing the sewage environment treatment audit standard is inconsistent with the time for providing the auxiliary sewage treatment evaluation information, so that auxiliary judgment requirement data in the auxiliary sewage treatment evaluation information is extracted according to a preset keyword extraction model, previous standard judgment requirement data is generated based on the sewage environment treatment audit standard, data feature iteration is performed on the previous standard judgment requirement data, and the updating requirement data between the auxiliary judgment requirement data and the previous standard judgment requirement data is generated, so that the data updating is realized.
Furthermore, incremental learning in incremental learning is performed on the sewage environment treatment auditing standard according to the updating requirement data, and a neural network model is used for updating the data, so that the accuracy of the generated updated sewage treatment auditing standard is improved.
In summary, the target to-be-processed areas selected according to a specific proportion in the preset original to-be-processed areas are sequentially acquired, and the area acquisition completion instruction is generated after the target to-be-processed areas are acquired, wherein the target to-be-processed areas include a first sewage to-be-optimized area, a sewage optimization advanced area and a second sewage to-be-optimized area, and the distance interval between every two of the first sewage to-be-optimized area, the sewage optimization advanced area and the second sewage to-be-optimized area is smaller than or equal to the preset standard interval distance; respectively acquiring sewage treatment effect data corresponding to the first sewage to-be-optimized area, the sewage optimization advanced area and the second sewage to-be-optimized area according to the area acquisition completion instruction based on a big data technology, wherein the sewage treatment effect data of the first sewage to-be-optimized area is first to-be-optimized data, the sewage treatment effect data of the sewage optimization advanced area is reference type to-be-optimized data, and the sewage treatment effect data of the second sewage to-be-optimized area is second to-be-optimized data; and performing data optimization processing on the first data to be optimized and the second data to be optimized according to the reference data to be optimized, and generating a data optimization report for storage based on the internet technology, so that on one hand, the sewage treatment data of an area in which superior sewage treatment is realized in a large area is optimized according to the sewage treatment data of the area in which superior sewage treatment is realized, and on the other hand, other areas in which sewage treatment is to be optimized in the large area are optimized, namely, the first data to be optimized and the second data to be optimized are optimized according to the data of a high-level area in the sewage treatment, so that the first data to be optimized and the second data to be optimized tend to the reference data to be optimized, and further, the simultaneous optimization of the sewage treatment in the large area is realized, and on the other hand, the efficient analysis and storage of the data are realized based on the large data and the internet technology, and further, and the efficiency of the sewage data treatment are improved.
In one embodiment, as shown in FIG. 2, an Internet and big data based sewage treatment system, the system comprising:
the system comprises a processing area module, a data processing module and a data processing module, wherein the processing area module is used for acquiring a target area to be processed selected according to a specific proportion in a preset original area to be processed and generating an area acquisition finishing instruction after the target area to be processed is acquired, the target area to be processed comprises a first sewage area to be optimized, a sewage optimization advanced area and a second sewage area to be optimized, and the distance interval between every two of the first sewage area to be optimized, the sewage optimization advanced area and the second sewage area to be optimized is smaller than or equal to a preset standard interval distance;
the data technology module is used for respectively acquiring sewage treatment effect data corresponding to the first sewage to-be-optimized area, the sewage optimization advanced area and the second sewage to-be-optimized area according to the area acquisition completion instruction based on a big data technology, wherein the sewage treatment effect data of the first sewage to-be-optimized area is first data to be optimized, the sewage treatment effect data of the sewage optimization advanced area is reference data to be optimized, and the sewage treatment effect data of the second sewage to-be-optimized area is second data to be optimized;
and the optimization processing module is used for performing data optimization processing on the first data to be optimized and the second data to be optimized according to the reference data to be optimized and generating a data optimization report to be stored based on the Internet technology.
In one embodiment, the processing region module is further configured to: acquiring a high-level region setting triggering instruction for triggering high-level region selection in an original region to be processed, acquiring an initial high-level region based on the high-level region setting triggering instruction, and simultaneously judging whether the initial high-level region meets a preset high-level region evaluation standard; if the initial advanced area meets the preset advanced area evaluation standard, extracting a target area meeting the advanced area evaluation standard in the initial advanced area, setting the target area as a sewage optimization advanced area, and acquiring basic environment data of the advanced area evaluation standard; acquiring a large-scale sewage treatment area which is in the same sewage treatment area as the sewage optimization advanced area in the original area to be treated based on the sewage optimization advanced area; screening a plurality of original sewage to-be-optimized areas in a circular area which is formed by taking the sewage optimization high-grade area as a core and outwards extending by taking a specific standard spacing distance as a radius according to the sewage treatment flow direction in the large-range sewage treatment area; respectively obtaining current actual environment data of each original sewage area to be optimized, comparing the current actual environment data with the basic environment data in similarity, and screening out the maximum value of the similarity numerical value and the second maximum value of the similarity numerical value; and setting the original sewage to-be-optimized area corresponding to the maximum value of the similarity value and the second maximum value of the similarity value as the first sewage to-be-optimized area and the second sewage to-be-optimized area.
In one embodiment, the optimization processing module is further configured to: acquiring a first incidence relation weighing value between the first sewage to-be-optimized region and the sewage optimization advanced region based on the reference type data to be optimized; acquiring a second incidence relation weighing value between the second sewage to-be-optimized region and the sewage optimization advanced region based on the reference type data to be optimized; acquiring a first additional influence value of the sewage optimization advanced region on the first sewage to-be-optimized region according to the first incidence relation weighing value; acquiring a second additional influence value of the sewage optimization advanced region on the first sewage to-be-optimized region according to the second incidence relation weighing value; generating a comprehensive additional influence value according to the first additional influence value and the second additional influence value, and extracting optimization processing data for performing data optimization on the first data to be optimized and the second data to be optimized according to the reference data to be optimized; filtering the comprehensive additional influence value from the optimized processing data, generating upgraded optimized processing data, performing data optimization processing on the first to-be-optimized data and the second to-be-optimized data based on the upgraded optimized processing data, and generating a data optimization report to be stored based on the internet technology; acquiring a high-grade area setting trigger instruction for triggering high-grade area selection in an original area to be processed, acquiring an initial high-grade area based on the high-grade area setting trigger instruction, and calling a sewage environment processing audit standard of an area where the initial high-grade area is located in real time; processing and judging the initial high-grade area based on the called sewage environment processing auditing standard, and generating an initial judging result; judging whether the initial judgment result meets a preset qualified judgment result value or not based on the generated initial judgment result; if the initial judgment result does not meet the preset qualified judgment result value, generating a reexamination judgment instruction, and searching objective natural environment influence data in a specific time period based on the reexamination judgment instruction; performing result correction processing on the initial judgment result based on the objective natural environment influence data, generating a reexamination judgment result, and meanwhile judging whether the reexamination judgment result meets a preset qualified judgment result value; if the re-review judgment result meets a preset qualified judgment result value, judging that the initial high-level region meets a preset high-level region evaluation standard; and if the re-examination and judgment result does not meet the preset qualified judgment result value, judging that the initial high-grade area does not meet the preset high-grade area evaluation standard.
In one embodiment, the optimization processing module is further configured to: acquiring auxiliary judgment information of sewage treatment; extracting auxiliary judgment requirement data in the auxiliary sewage treatment judgment information according to a preset keyword extraction model based on the auxiliary sewage treatment judgment information, and generating previous standard judgment requirement data based on the sewage environment treatment auditing standard; performing data feature iteration on the previous standard evaluation requirement data based on the auxiliary evaluation requirement data, and generating update requirement data between the auxiliary evaluation requirement data and the previous standard evaluation requirement data; and performing incremental learning on the sewage environment treatment auditing standard according to the updating requirement data, and generating an updated sewage treatment auditing standard.
In one embodiment, as shown in fig. 3, a computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the sewage treatment method based on the internet and big data when executing the computer program.
A computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the above-described internet-and big-data-based sewage treatment method.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
It should be noted that, in the embodiment of the computer device, the included units and modules are merely divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
All possible combinations of the technical features in the above embodiments may not be described for the sake of brevity, but should be considered as being within the scope of the present disclosure as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is specific and detailed, but not to be understood as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, and these are all within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (6)

1. A sewage treatment method based on Internet and big data is characterized by comprising the following steps:
acquiring a target area to be processed selected according to a specific proportion in a preset original area to be processed, and generating an area acquisition completion instruction after the target area to be processed is acquired, wherein the target area to be processed comprises a first area to be optimized for sewage, a high-grade area for sewage optimization and a second area to be optimized for sewage, and the distance interval between every two of the first area to be optimized for sewage, the high-grade area for sewage optimization and the second area to be optimized for sewage is less than or equal to a preset standard interval distance; respectively acquiring sewage treatment effect data corresponding to the first sewage to-be-optimized area, the sewage optimization advanced area and the second sewage to-be-optimized area according to the area acquisition completion instruction based on a big data technology, wherein the sewage treatment effect data of the first sewage to-be-optimized area is first to-be-optimized data, the sewage treatment effect data of the sewage optimization advanced area is reference type to-be-optimized data, and the sewage treatment effect data of the second sewage to-be-optimized area is second to-be-optimized data; performing data optimization processing on the first data to be optimized and the second data to be optimized according to the reference data to be optimized, and generating a data optimization report to be stored based on the Internet technology;
acquiring a target area to be processed selected according to a specific proportion from a preset original area to be processed, and generating an area acquisition completion instruction after the target area to be processed is acquired, wherein the target area to be processed comprises a first area to be optimized for sewage, a high-grade area for sewage optimization and a second area to be optimized for sewage, and the distance interval between every two areas of the first area to be optimized for sewage, the high-grade area for sewage optimization and the second area to be optimized for sewage is less than or equal to a preset standard interval distance; the method specifically comprises the following steps: acquiring a high-level region setting triggering instruction for triggering high-level region selection in an original region to be processed, acquiring an initial high-level region based on the high-level region setting triggering instruction, and simultaneously judging whether the initial high-level region meets a preset high-level region evaluation standard; if the initial advanced area meets the preset advanced area evaluation standard, extracting a target area meeting the advanced area evaluation standard in the initial advanced area, setting the target area as a sewage optimization advanced area, and acquiring basic environment data of the advanced area evaluation standard; acquiring a large-scale sewage treatment area which is in the same sewage treatment area as the sewage optimization advanced area in the original area to be treated based on the sewage optimization advanced area; screening a plurality of original sewage areas to be optimized in a circular area formed by outwards extending by taking the sewage optimization advanced area as a core and taking a specific standard spacing distance as a radius according to the sewage treatment flow direction in the large-range sewage treatment area; respectively obtaining current actual environment data of each original sewage area to be optimized, comparing the current actual environment data with the basic environment data according to the similarity, and screening out the maximum value of the similarity numerical value and the second maximum value of the similarity numerical value; setting the original sewage to-be-optimized area corresponding to the maximum value of the similarity value and the second maximum value of the similarity value as the first sewage to-be-optimized area and the second sewage to-be-optimized area;
acquiring a high-level region setting triggering instruction for triggering high-level region selection in an original region to be processed, acquiring an initial high-level region based on the high-level region setting triggering instruction, and simultaneously judging whether the initial high-level region meets a preset high-level region evaluation standard; the method specifically comprises the following steps:
acquiring a high-grade area setting trigger instruction for triggering high-grade area selection in an original area to be processed, acquiring an initial high-grade area based on the high-grade area setting trigger instruction, and calling a sewage environment processing audit standard of an area where the initial high-grade area is located in real time; processing and judging the initial high-grade area based on the called sewage environment processing auditing standard, and generating an initial judging result; judging whether the initial judgment result meets a preset qualified judgment result value or not based on the generated initial judgment result; if the initial judgment result does not meet the preset qualified judgment result value, generating a reexamination judgment instruction, and searching objective natural environment influence data in a specific time period based on the reexamination judgment instruction; performing result correction processing on the initial judgment result based on the objective natural environment influence data, generating a reexamination judgment result, and meanwhile judging whether the reexamination judgment result meets a preset qualified judgment result value; if the re-review judgment result is judged to meet a preset qualified judgment result value, judging that the initial high-level region meets a preset high-level region evaluation standard; and if the re-review result does not meet the preset qualified result value, judging that the initial high-level region does not meet the preset high-level region evaluation standard.
2. The internet and big data based sewage treatment method according to claim 1, wherein the first data to be optimized and the second data to be optimized are subjected to data optimization processing according to the reference data to be optimized, and data optimization reports are generated and stored based on internet technology; the method specifically comprises the following steps:
acquiring a first incidence relation weighing value between the first sewage to-be-optimized region and the sewage optimization advanced region based on the reference type data to be optimized; acquiring a second incidence relation weighing value between the second sewage to-be-optimized region and the sewage optimization advanced region based on the reference type data to be optimized; acquiring a first additional influence value of the sewage optimization advanced region on the first sewage to-be-optimized region according to the first incidence relation weighing value; acquiring a second additional influence value of the sewage optimization advanced region on the first sewage to-be-optimized region according to the second incidence relation weighing value; generating a comprehensive additional influence value according to the first additional influence value and the second additional influence value, and extracting optimization processing data for performing data optimization on the first data to be optimized and the second data to be optimized according to the reference data to be optimized; and filtering the comprehensive additional influence value from the optimization processing data, generating upgrade optimization processing data, performing data optimization processing on the first data to be optimized and the second data to be optimized based on the upgrade optimization processing data, and generating a data optimization report to be stored based on the internet technology.
3. The internet and big data based sewage treatment method according to claim 1, wherein a high-level zone setting triggering instruction for triggering high-level zone selection in an original area to be treated is obtained, an initial high-level zone is obtained based on the high-level zone setting triggering instruction, and simultaneously a sewage environment treatment auditing standard of an area where the initial high-level zone is located is called in real time; and then also comprises the following steps:
acquiring auxiliary judgment information of sewage treatment; extracting auxiliary judgment requirement data in the auxiliary sewage treatment judgment information according to a preset keyword extraction model based on the auxiliary sewage treatment judgment information, and generating previous standard judgment requirement data based on the sewage environment treatment auditing standard; performing data characteristic iteration on the previous standard evaluation requirement data based on the auxiliary evaluation requirement data, and generating update requirement data between the auxiliary evaluation requirement data and the previous standard evaluation requirement data; and performing incremental learning on the sewage environment treatment auditing standard according to the updating requirement data, and generating an updated sewage treatment auditing standard.
4. An internet and big data based sewage treatment system, the system comprising:
the system comprises a processing area module, a data processing module and a data processing module, wherein the processing area module is used for acquiring a target area to be processed selected according to a specific proportion in a preset original area to be processed and generating an area acquisition completion instruction after the target area to be processed is acquired, the target area to be processed comprises a first sewage area to be optimized, a sewage optimization advanced area and a second sewage area to be optimized, and the distance interval between every two of the first sewage area to be optimized, the sewage optimization advanced area and the second sewage area to be optimized is smaller than or equal to a preset standard interval distance;
the data technology module is used for respectively acquiring sewage treatment effect data corresponding to the first sewage to-be-optimized area, the sewage optimization advanced area and the second sewage to-be-optimized area according to the area acquisition completion instruction based on a big data technology, wherein the sewage treatment effect data of the first sewage to-be-optimized area is first data to be optimized, the sewage treatment effect data of the sewage optimization advanced area is reference type data to be optimized, and the sewage treatment effect data of the second sewage to-be-optimized area is second data to be optimized;
the optimization processing module is used for performing data optimization processing on the first data to be optimized and the second data to be optimized according to the reference data to be optimized and generating a data optimization report to be stored based on the Internet technology;
the optimization processing module is further configured to: acquiring a first incidence relation weighing value between the first sewage to-be-optimized region and the sewage optimization advanced region based on the reference type data to be optimized; acquiring a second incidence relation weighing value between the second sewage to-be-optimized region and the sewage optimization advanced region based on the reference type data to be optimized; acquiring a first additional influence value of the sewage optimization advanced region on the first sewage to-be-optimized region according to the first incidence relation weighing value; acquiring a second additional influence value of the sewage optimization advanced region on the first sewage to-be-optimized region according to the second incidence relation weighing value; generating a comprehensive additional influence value according to the first additional influence value and the second additional influence value, and extracting optimization processing data of data to be optimized on the first data to be optimized and the second data to be optimized according to the reference data to be optimized; filtering the comprehensive additional influence value from the optimized processing data, generating upgraded optimized processing data, performing data optimization processing on the first to-be-optimized data and the second to-be-optimized data based on the upgraded optimized processing data, and generating a data optimization report to be stored based on the internet technology; acquiring a high-grade area setting triggering instruction for triggering high-grade area selection in an original area to be processed, acquiring an initial high-grade area based on the high-grade area setting triggering instruction, and calling a sewage environment processing auditing standard of an area where the initial high-grade area is located in real time; processing and judging the initial high-grade area based on the called sewage environment processing auditing standard, and generating an initial judging result; judging whether the initial judgment result meets a preset qualified judgment result value or not based on the generated initial judgment result; if the initial judgment result does not meet the preset qualified judgment result value, generating a reexamination judgment instruction, and searching objective natural environment influence data in a specific time period based on the reexamination judgment instruction; performing result correction processing on the initial judgment result based on the objective natural environment influence data to generate a reexamination judgment result, and meanwhile judging whether the reexamination judgment result meets a preset qualified judgment result value or not; if the re-review judgment result is judged to meet a preset qualified judgment result value, judging that the initial high-level region meets a preset high-level region evaluation standard; if the re-review judgment result does not meet the preset qualified judgment result value, judging that the initial high-level region does not meet the preset high-level region evaluation standard;
the processing region module is further configured to: acquiring a high-level region setting trigger instruction for triggering high-level region selection in an original region to be processed, acquiring an initial high-level region based on the high-level region setting trigger instruction, and judging whether the initial high-level region meets a preset high-level region evaluation standard; if the initial advanced area meets the preset advanced area evaluation standard, extracting a target area meeting the advanced area evaluation standard in the initial advanced area, setting the target area as a sewage optimization advanced area, and acquiring basic environment data of the advanced area evaluation standard; acquiring a large-scale sewage treatment area which is in the same sewage treatment area as the sewage optimization advanced area in the original area to be treated based on the sewage optimization advanced area; screening a plurality of original sewage areas to be optimized in a circular area formed by outwards extending by taking the sewage optimization advanced area as a core and taking a specific standard spacing distance as a radius according to the sewage treatment flow direction in the large-range sewage treatment area; respectively obtaining current actual environment data of each original sewage area to be optimized, comparing the current actual environment data with the basic environment data according to the similarity, and screening out the maximum value of the similarity numerical value and the second maximum value of the similarity numerical value; and setting the original sewage to-be-optimized region corresponding to the maximum value of the similarity value and the second maximum value of the similarity value as the first sewage to-be-optimized region and the second sewage to-be-optimized region.
5. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor realizes the steps of the method of any one of claims 1 to 3 when executing the computer program.
6. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 3.
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