CN110363319B - Resource allocation method, server, resource claim method and client - Google Patents
Resource allocation method, server, resource claim method and client Download PDFInfo
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Abstract
The application provides a resource allocation method, a server, a resource claim method and a client, wherein the resource allocation method comprises the following steps: acquiring historical empty data of the allocated resources; predicting the resources in the empty state in the allocated resources in the target time period according to the historical empty data; and distributing the predicted use right of the resource in the empty state in the target time period. The technical problem of the existing resource waste is solved through the scheme, and the technical effect of effectively improving the resource utilization rate is achieved.
Description
Technical Field
The application belongs to the technical field of Internet, and particularly relates to a resource allocation method, a server, a resource claim method and a client.
Background
In daily life and work, many resources are often allocated to users in advance. For example, if the parking space a is allocated to the user X by preempting or drawing for one year, the user X has one year of the right to use the parking space a. In the year, the users other than the user X have no authority to use the parking space.
However, in one year (e.g., 365 days), user X may only need to use the parking space for 200 days, and the rest of the days is hundred days, the parking space A is idle, and even if the parking space A is in an idle state, other users have no authority to use the parking space A, so that the waste of parking space resources is necessarily caused.
Not only for parking spaces, but also for other resources occupied by a certain or some fixed user groups according to a period of time, the problem of resource waste often exists.
No effective solution has been proposed to this problem.
Disclosure of Invention
The application aims to provide a resource allocation method, a server, a resource claim method and a client so as to improve the utilization rate of resources.
The application provides a resource allocation method, a server, a resource claim method and a client which are realized as follows:
a resource allocation method, comprising:
acquiring historical empty data of the allocated resources;
predicting the resources in the empty state in the allocated resources in the target time period according to the historical empty data;
and distributing the predicted use right of the resource in the empty state in the target time period.
A resource allocation method, comprising:
receiving a claim request of the use right of the empty resource in the target time period, wherein the empty resource is the resource which is allocated but not used in the target time period;
and according to the claim request, issuing the use authority of the target time period to the blank resource to a claimant.
A resource claim method, comprising:
displaying a first interface;
receiving a resource claim request input by a user on the first interface, wherein the resource claim request carries a target time period for requesting use, and the claim request is used for requesting the use right of the resource in the allocated resource in an empty state in the target time period;
and displaying the claim result.
A resource allocation server comprising a processor and a memory for storing processor executable instructions, the processor implementing the steps of the above method when executing the instructions.
A client, comprising: a processor, and a display, wherein,
the display is used for displaying a first interface;
the processor is used for receiving a resource claim request input by a user at the first interface, wherein the resource claim request carries a target time period for requesting use, and the claim request is used for requesting the use right of the resource in the allocated resource in an empty state in the target time period;
The display is also used for displaying the claim result.
A computer readable storage medium having stored thereon computer instructions which when executed perform the steps of the above method.
According to the resource allocation method provided by the application, the resources in the empty state in the allocated resources in the target time period are predicted and obtained based on the historical empty data of the allocated resources, and then the use rights of the resources are allocated again, so that the technical problem of resource waste is effectively solved, and the technical effect of effectively improving the resource utilization rate is achieved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present application, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a resource allocation system according to the present application;
FIG. 2 is a schematic diagram of a resource allocation system according to the present application;
FIG. 3 is a schematic illustration of a parking system of the parking space system provided by the present application;
FIG. 4 is a schematic illustration of a parking system of the parking space system provided by the present application;
FIG. 5 is a flow chart of a method for parking spot reassignment provided by the present application;
FIG. 6 is a schematic diagram of a parking space resource allocation system provided by the application;
FIG. 7 is a schematic view of a parking space claim interface provided by the application;
FIG. 8 is a flow chart of a resource allocation method provided by the present application;
FIG. 9 is another method flow diagram of a resource allocation method provided by the present application;
FIG. 10 is a flow chart of a resource claim method provided by the present application;
FIG. 11 is a schematic diagram of a server-side architecture according to the present application;
fig. 12 is a schematic diagram of a client architecture according to the present application.
Detailed Description
In order to make the technical solution of the present application better understood by those skilled in the art, the technical solution of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, shall fall within the scope of the application.
The reason why the problem of resource waste occurs is considered to be that, in view of the problem of resource waste existing in the existing resource allocation, after the resource is allocated to a part of people in a complete period of time, other people who are not allocated have no authority to use the resource in the idle state even if the allocated resource is in the idle state.
For example, the parking space allocation mode adopted by company B is to apply for and allocate parking spaces according to the unit of year, in order to ensure that vehicles which have successfully applied for parking spaces can be parked, vehicles which have not applied for parking spaces in the year cannot enter the company B for parking, and the vehicle access control system cannot recognize vehicles which have not allocated parking spaces, so that vehicles cannot be released. However, assuming that there are 100 parking spaces in company B, the actual daily occupancy is at most 80%, that is, even if a part of the vehicles is allowed to enter again, the parking spaces of company B are digestible.
In view of the above, the embodiments of the present application consider that if the number of resources or the possible idle positions of resources on the day or the next day can be predicted based on the history of use of the resources, and the individual requests of the individual resource claimants, etc., and the resources are provided to users who have not successfully claiming the resources for claiming, so that the users can temporarily acquire the resource usage rights for a period of time. The method can solve the problem of resource waste on one hand and can improve user experience on the other hand. Referring to fig. 1, an embodiment of the present application provides a resource allocation system, which may include: a resource allocation server 101 and a client 102. Wherein the client 102 may specifically be connected to the resource allocation server 101 through a wired or wireless network. Specifically, the resource allocation server 101 may predict a free resource within a specified time period (or a target time period) based on a historical usage record of the resource (e.g., historical empty data of the allocated resource), and may provide the free resource to a user that is not declared to the resource for declaring usage rights for the free period of the free resource. The resource allocation server 101 may push the predicted and integrated idle resources, idle periods, and the like to the client 102, and the client 102 may claim the usage rights of the idle periods for the idle resource amounts.
In an embodiment, the resource allocation server may be a single server, may be a server cluster, may be a cloud processor, or the like, and specifically, which mode may be adopted may be selected according to actual needs.
In one embodiment, the client may be a terminal device or software used by a user. Specifically, the client may specifically be a terminal device such as a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart watch, or other wearable devices. Of course, the client may also be software that can be run in the terminal device described above. For example: nails, payment treasures or other application software.
In one embodiment, the resource allocation server may be coupled to an associated database through which historical usage records of the resource are obtained. Of course, the database described above is only a schematic illustration. Specifically, the server side may be further connected to a collection side of related data, where the collection side collects the related data as the history usage record.
Factors affecting resource usage are also different considering that for different resources. For example, if the resource is a basketball court of a school, the factors affecting the use of the resource may include course arrangement of the school, activity arrangement of the school, holidays, whether the user requests, etc., and when the history of use is obtained to predict the empty status of the basketball court of the school, the resource allocation server may be accessed to an attendance system, a course arrangement system, etc. of the school to obtain corresponding factor data, so as to effectively predict the empty status of the basketball court.
For example, if the resource is a parking space of a company, factors influencing the empty situation of the parking space mainly include holiday situation, employee's leave situation, weather situation, business trip situation, etc., so that when the empty situation of the allocated parking space is predicted, the resource allocation server can be accessed into a parking space system, a personnel system, a attendance system, a leave system, a travel system, etc. to obtain the influencing factor data influencing the empty situation of the parking space, thereby effectively predicting the empty situation of the parking space. For example: the weather information corresponding to the allocated parking spaces in the using state and the weather information corresponding to the allocated parking spaces in the vacant state can be collected through the weather system. According to the method, the resource allocation server can acquire and use the usage records of the allocated parking spaces, the characteristic information of the users and the environment information during use and/or idle time as historical data, so that the correlations between idle conditions and factors can be obtained through subsequent statistics.
In one embodiment, considering that when predicting and releasing the empty resources, if traversing all the resources each time tends to increase the calculation amount, a memory may be provided for storing the information of the predicted empty resources, as shown in fig. 2, the memory is used as a shared resource pool, that is, the user may claim the resources in the shared resource pool from the memory.
For example, the resource allocation server may predict that the usage probabilities of the allocated parking spaces with numbers a21 and a93 in the parking area on two days are 2% and 5% respectively, and are smaller than a probability threshold (the probability threshold may be understood as a reference data determined according to historical data, and when the usage probability of a certain resource is smaller than the probability threshold, the resource may be considered to be in a more likely empty state) 10%, so that the two allocated parking spaces may be determined as the allocable parking spaces on two days now, i.e. the parking spaces meeting the requirement, and the two parking spaces may be released into the shared parking space pool, so that the applicant may find the two temporarily usable parking spaces in time through the connection between the client and the shared parking space pool, so as to apply for usage.
In one embodiment, the resource allocation server may obtain a prediction model according to analysis and integration of the historical data, and may predict a vacant condition of a specific resource through the prediction model, for example, may predict a vacant condition of a specific parking space or a specific office location, and may then provide the predicted vacant period of the parking space or the office location to other users for claiming. However, considering that the accuracy of prediction for a specific resource is obviously easy to occur when the predicted result does not match the actual result. For this purpose, consider if for a large amount of resources, for example: one thousand parking spaces, five hundred office spaces, etc., and the large amount of resources predicts the possible empty rate of the amount of resources in a certain time period, and the prediction result obviously is more relevant to the actual situation.
Based on this, probabilistic prediction of large data can be employed in consideration of a situation where prediction for a certain specific resource empty situation is inaccurate. For example, if there are thousands of parking spaces, prediction is performed based on historical data, prediction results in that the date of 2018 is 2 and 12, and the empty rate of the parking spaces is 20%, that is, if 200 parking spaces are in an empty state, then the resource allocation server may issue the usage rights of not more than 200 parking spaces in the date of 2018 is 2 and 12, and the user claims the usage rights. The parking spaces can also be distributed according to areas, for example, as shown in fig. 3 and 4, the parking area is divided into area a and area B … …, each area has ten parking spaces, 1 empty space is predicted to be available in area a, 0 empty space is predicted to be available in area B, 3 empty spaces … … are available in area C, and then the resource allocation server can issue the empty spaces in the manner of empty conditions of each area, so that a claimant user can claim the empty spaces in the parking area more suitable according to the distance from the office area of the claimant user, and user experience is effectively improved.
In one embodiment, the resource allocation server may extract characteristic information of the applicant from the parking space usage application, in addition to acquiring the specified time period (or the target time period) from the parking space usage application. For example, the location information of the applicant, the identity information of the applicant, and the custom information of the applicant.
Taking parking space allocation as an example, the resource allocation server can extract the position information of the applicant from the parking space application, so that the parking space closest to the applicant can be selected from a plurality of parking spaces meeting the requirements as the recommended parking space according to the position information of the applicant, and the use authority of the recommended parking space is sent to the client. In addition, the applicant can set a user-defined requirement through the client according to specific conditions while generating a parking space use application through the client. For example, the underground garage and the free parking can be selected as custom requirements (i.e., custom requirements) through an interface of a mobile phone parking stall application. When the server side is in specific implementation, the user-defined requirements can be combined to screen the parking spaces meeting the requirements of the underground garage and free parking from the plurality of parking spaces meeting the requirements as recommended parking spaces, and the recommended parking spaces are provided for the applicant for temporary use.
Furthermore, the method predicts the use condition of the single resource and allocates the single empty resource meeting the requirements, so that once the single resource is predicted incorrectly, the single resource is directly provided for the applicant, inconvenience is caused to the applicant, and the experience of the applicant is reduced. For example, the prediction model predicts that the B121 parking space allocated to the resident T in the cell is in the empty state during the period of 2:00 pm to 5:00 pm on monday, but in reality, the resident T is not going out for the time of the family, and occupies the B121 parking space. At this time, when the method is implemented, the B121 parking space is determined as an empty resource, and the parking space is allocated to an applicant who needs to temporarily use the parking space. However, when the applicant parks, the applicant finds that the parking space B121 cannot be used, and can only apply for searching for a new parking space again, so that the time of the applicant is delayed, inconvenience is caused to the applicant, and the use experience of the applicant is reduced.
In view of the above, in one embodiment, the original prediction for a single resource that meets the requirements may be further improved to the prediction for a resource region that meets the requirements. The above-mentioned resource area is distinguished from a single resource which is free to be satisfied, and it is understood that the resource area which is satisfied includes a plurality of resource which is free to be satisfied. For example, an available space may be understood as a single, desirably empty resource, and a parking area comprising a plurality of available spaces may be understood as a desirably resource area. Specifically, the use probability of each resource in each resource area in a specified time period can be predicted by using a prediction model according to the history record; determining a resource region with the use probability smaller than the threshold probability and the number of the resources meeting the requirements being larger than the threshold number in a specified time period as a resource region meeting the requirements; furthermore, the access authority of the resource region meeting the requirements can be distributed to the applicant, so that the applicant can use the access authority to enter the resource region meeting the requirements to search for the really usable empty resources from a plurality of resources meeting the requirements to be determined for use.
For example, the prediction model may be used to predict the use probability of each parking space in 5 parking space areas (area a, area B, area C, area D, area E) in the cell in a specified time period, determine a parking space with a use probability of less than 10% in each parking space as an available parking space, and use an area C with a number of available parking spaces greater than 3 in only one of the 5 parking space areas as an available parking space area. In the appointed time period, if an applicant temporarily applies for using the vehicle, the system can send the access authority of the C area to the applicant in an access permission mode, and send 301 vehicle spaces, 3014 vehicle spaces, 327 vehicle spaces and 384 vehicle spaces which are predicted to be used in the C area and have the use probability of less than 10% in the time period to the applicant as recommended available vehicle spaces together, so that the applicant can find a truly usable vehicle space in a plurality of available vehicle spaces to be determined in the C area in a targeted manner. The applicant can enter the area C by means of the entering permission to find the available parking space. Of course, the system may just send the prompt message to the applicant: the available parking spaces exist in the area C, information of the recommended parking space positions in the area C is given to the applicant, and the system sends identity information of the applicant, such as license plates of automobiles driven by the applicant, to a barrier gate system in the area C. Therefore, the applicant can firstly drive the vehicle to the C area according to the prompt information, and the barrier gate system of the C area can compare the license plate number of the applicant with the license plate number sent by the system, and the vehicle is opened and released after the consistency is confirmed.
In this example, by predicting the empty resource in the allocated resources and reassigning the predicted empty resource, the empty rate of the resource can be effectively reduced, and the utilization condition of the resource can be improved.
The above-mentioned resource allocation mode is mainly described by taking basketball courts, parking spaces and the like as resource types, and when in actual implementation, the resources can be specifically: office location resources, server resources, office equipment resources, court resources, conference room resources, fitness equipment resources, learning resources and the like, and when the method is implemented, other types of resources can be introduced as the resources according to specific scenes. The present application is not limited to this.
In the following, a parking space in an enterprise is used as a specific scene to describe, and the parking space can be allocated to staff in the modes of claim, robbery and lottery on the assumption that the parking space in an office area of an enterprise is relatively scarce. For example, each allocation is to allocate half a year of usage rights to the parking space to employees, i.e., employees who have successfully applied for the parking space have half a year of usage rights to the parking space. However, after analysis of the parking data, it is found that the average parking space utilization rate of 7 months is about 93%, and staff having the parking space may not enter the office area for business trip, leave, etc., especially on monday and friday, the parking space availability rate is relatively higher. Therefore, in order to improve the utilization rate of the parking space, more staff can have the opportunity to use the parking space. The past year parking data can be learned through training to predict each parking stall in the office area of the next day and the empty parking stalls in the parking stall area, then, the empty parking stalls are placed in the shared parking stall pool, and the parking stalls in the shared parking stall pool can be provided for staff with parking stall use requirements through intelligent parking application. In order to improve the efficiency of parking stall use, when certain staff applies for the use, the parking stall distribution system can do primary screening in sharing parking stall pond, and the priority distributes the nearest parking stall of this staff's station, gives corresponding banister with the license plate issuing permission of this staff simultaneously.
That is, in this example, the number of empty parking spaces on the t+1 day can be predicted by using a data+machine learning method, and the empty parking spaces are released for application by required staff, so as to improve the utilization rate of the parking spaces. Specifically, data such as business trip, leave, weather, garden entering condition, date state, road control and the like can be collected so as to analyze the service condition of vehicles in an office area, and the characteristics are selected through correlation analysis to perform model training. For example, 80% of training set and 20% of testing set can be split, the models are trained by using a grid search and cross verification mode, two models of linear regression and GBDT (Gradient Boosting Decision Tree) regression are selected for comparison evaluation, and in the model evaluation, GBDT regression algorithm is better than the linear regression model, so that a GBDT regression model can be selected to predict a t+1 day vehicle entering a garden, and an empty parking space is released to needed personnel for preemption through a parking system.
When the method is implemented, as shown in fig. 5, firstly, data acquisition, namely historical use records of parking spaces, are acquired, then the data are cleaned to remove error data and the like, then a prediction model is obtained based on training of the data, the obtained empty parking spaces are predicted based on the prediction model, and then the empty parking spaces are released for the user to preempt.
That is, the machine learns the historical usage record, and uses the predicted available space as a reusable resource, where the historical space usage information may be as shown in fig. 6, including one or more of the following data:
1) The vehicle owner information, the corresponding license plate, the garage corresponding to the license plate and the parking space are acquired from the parking space system;
2) Whether the owner of the vehicle obtained from the human resource system is away from duty or not, the home composition of the owner of the vehicle (for example: whether there are children, etc.);
3) A record of public holidays and business days acquired from the holiday system (for example: saturday may be a workday), enterprise events, etc.;
4) Acquiring a station allocated to a vehicle owner from a station system;
5) The attendance records of the car owners are obtained from the access control system;
6) The method comprises the steps of acquiring a vehicle owner leave record and a submitted leave application form from a leave system;
7) A record of the vehicle owner's business trip and a submitted business trip application form obtained from the business trip system.
In other words, when the method is implemented, the accuracy of a prediction model obtained by training is higher based on factor data such as business trip, leave, job departure, line restriction, weather, continuous leave, extra-large event, family composition and the like.
Furthermore, after the empty parking spaces are predicted, the empty parking spaces can be classified for other staff to claim, and the license plate rights of the vehicle owners who rob the parking spaces are issued to the barrier through the barrier system. Fig. 7 is a schematic diagram of an interface for a user to claim a parking space.
The embodiment of the application also provides a resource allocation method. It should be noted that although the present application provides a method operation step or apparatus structure as shown in the following embodiments or the accompanying drawings, more or fewer operation steps or module units may be included in the method or apparatus based on conventional or non-inventive labor. In the steps or structures where there is no necessary causal relationship logically, the execution order of the steps or the module structure of the apparatus is not limited to the execution order or the module structure shown in the drawings and the description of the embodiments of the present application. The described methods or module structures may be implemented sequentially or in parallel (e.g., in a parallel processor or multithreaded environment, or even in a distributed processing environment) in accordance with the embodiments or the method or module structure connection illustrated in the figures when implemented in a practical device or end product application.
As shown in fig. 8, a method for allocating resources according to an embodiment of the present application may include the following steps:
step 801: acquiring historical empty data of the allocated resources;
step 802: predicting the resources in the empty state in the allocated resources in the target time period according to the historical empty data;
Step 803: and distributing the predicted use right of the resource in the empty state in the target time period.
According to the resource allocation method provided by the application, the resources in the empty state in the allocated resources in the target time period are predicted and obtained based on the historical empty data of the allocated resources, and then the use rights of the resources are allocated again, so that the technical problem of the existing resource waste is effectively solved, and the technical effect of effectively improving the resource utilization rate is achieved.
In order to realize effective prediction of the empty resources, a prediction model can be established, and the empty conditions of the allocated resources can be predicted by using the prediction model. Specifically, predicting, according to the historical idle data, a resource in an idle state in the allocated resources in the target time period may include: training to obtain a blank resource prediction model according to the historical blank data; and predicting and obtaining the resources in the empty state in the allocated resources in the target time period through the prediction model.
In particular, the historical vacancy data may include, but is not limited to, at least one of: characteristic data of a resource assigner, blank condition data of an assigned resource and influence factor data of whether the resource can be used. The above-mentioned resources in the idle state may include, but are not limited to, one of the following: a single resource amount of resources, and a resource region containing a plurality of resource amounts. The allocated resources may include, but are not limited to, at least one of: parking space resources, office location resources, server resources, office equipment resources, court resources, meeting room resources, fitness equipment resources, learning resources, and the like. Of course, the various sources listed above are only illustrative and should not be construed as unduly limiting embodiments of the application.
In one embodiment, the allocating the predicted usage rights of the resource in the idle state for the target period may include: and opening the use right in the target time period for the user claiming the use right.
As shown in fig. 9, a resource allocation method according to another embodiment of the present application, which is described from a claim point of view, may include the following steps:
step 901: receiving a claim request of the use right of the empty resource in the target time period, wherein the empty resource is the resource which is allocated but not used in the target time period;
step 902: and according to the claim request, issuing the use authority of the target time period to the blank resource to a claimant.
Specifically, the issuing, by the step 902, the usage rights of the empty resource for the target time period to the claimant according to the claimant request may include:
s1: acquiring characteristic data of a claimant;
s2: determining the empty resource which is most matched with the claimant in a plurality of empty resources according to the characteristic data;
s3: and sending the determined use permission of the empty resource in the target time period to the claimant.
By the allocation mode, the resource allocation efficiency and the user experience can be effectively improved.
In order to reduce the calculation amount of the system, a shared resource pool may be set, and accordingly, determining, according to the feature data, an empty resource that is most matched with the claimant from among a plurality of empty resources may include: and searching for the empty resources which are most matched with the claimant from a shared resource pool, wherein all predicted resources which are allocated but not used in a target time period are stored in the shared resource pool.
Specifically, referring to fig. 7 and referring to fig. 10, the present application further provides a resource claim method, which is described from the client side and may include the following steps.
S1001: displaying a first interface;
s1002: receiving a resource claim request input by a user on the first interface, wherein the resource claim request carries a target time period for requesting use, and the claim request is used for requesting the use right of the resource in the allocated resource in an empty state in the target time period;
s1003: and displaying the claim result.
In this embodiment, the first interface may be specifically understood as a resource declaration interface. Specifically, referring to the display interface shown in fig. 7, the user may fill the usage time of the claim in the "usage time" column on the interface as the target time period, and then click the "parking space application" to send the claim request to the server. The server may then receive the resource claim request carrying the target time period for use, so as to determine, according to the claim request, whether the resource in the idle state exists in the target time period and may be allocated to the user.
In one embodiment, the claim result may specifically include: whether or not the declaration was successful, the reason for the failure, the resource information of the resource that was declared successful, and the like. Of course, it should be noted that the above-listed claims are merely illustrative. In the specific implementation, other information may be displayed as a claim result according to a specific scene.
In one embodiment, after receiving the resource claim request input by the user at the first interface, the method may further include the following when implemented:
s1: displaying a plurality of resources which are in a vacant state in the target time period in the allocated resources;
s2: receiving a selection instruction of a user for the plurality of resources;
s3: and allocating the use right of the resource selected by the selection instruction to the user.
In this embodiment, in the allocated resources during implementation, there may be a plurality of resources in an idle state in the target time period, and at this time, the plurality of resources in the idle state may be displayed to the user by the client for the user to select. Thus, the user can select the resource claim suitable for the user according to the user's own situation and personal preference through the selection instruction. The selection instruction may specifically be a click or a hook of a user on a preferred resource in the plurality of resources. Therefore, the server can acquire and distribute the use right of the resources suitable for the user according to the selection instruction of the user, so that the use experience of the user can be improved.
The method embodiments provided by the embodiments of the present application may be performed in a mobile terminal, a computer terminal, or similar computing device. Taking the operation on the server side as an example, fig. 11 is a block diagram of the hardware structure of the server side of a resource allocation method according to an embodiment of the present application. As shown in fig. 11, the resource allocation server 11 may include one or more (only one is shown in the figure) processors 1102 (the processor 1102 may include, but is not limited to, a microprocessor MCU or a processing device such as a programmable logic device FPGA), a memory 1104 for storing data, and a transmission module 1106 for communication functions. It will be appreciated by those of ordinary skill in the art that the configuration shown in fig. 11 is merely illustrative and is not intended to limit the configuration of the electronic device described above. For example, the resource allocation server 11 may also include more or fewer components than shown in fig. 11, or have a different configuration than shown in fig. 11.
The memory 1104 may be used to store software programs and modules of application software, such as program instructions/modules corresponding to the resource allocation method in the embodiment of the present application, and the processor 1102 executes the software programs and modules stored in the memory 1104 to perform various functional applications and data processing, that is, implement the resource allocation method of the application program. Memory 1104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, memory 1104 may further include memory located remotely from processor 1102, which may be connected to computer terminal 11 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission module 1106 is used to receive or transmit data via a network. The specific example of the network described above may include a wireless network provided by a communication provider of the computer terminal 11. In one example, the transmission module 1106 includes a network adapter (Network Interface Controller, NIC) that can connect to other network devices via a base station to communicate with the internet. In one example, the transmission module 1106 may be a Radio Frequency (RF) module for communicating with the internet wirelessly.
At the software level, the resource allocation device may include: the system comprises an acquisition module, a prediction module and an allocation module, wherein:
the acquisition module is used for acquiring historical vacant data of the allocated resources;
the prediction module is used for predicting the resources in the empty state in the allocated resources in the target time period according to the historical empty data;
and the allocation module is used for allocating the predicted usage rights of the resources in the empty state for the target time period.
In one embodiment, the prediction module may specifically train to obtain a blank resource prediction model according to the historical blank data; and predicting and obtaining the resources in the empty state in the allocated resources in the target time period through the prediction model.
In one embodiment, the historical blank data may include, but is not limited to, at least one of: characteristic data of a resource assigner, blank condition data of an assigned resource and influence factor data of whether the resource can be used.
In one embodiment, the resources in the idle state may include, but are not limited to, at least one of the following: a single resource amount of resources, and a resource region containing a plurality of resource amounts.
In one embodiment, the allocation module may specifically open the usage rights in the target period for the user claiming the usage rights.
In one embodiment, the allocated resources may include, but are not limited to, at least one of: parking space resources, office location resources, server resources, office equipment resources, court resources, meeting room resources, fitness equipment resources, learning resources, and the like.
At the software level, the resource allocation device may further include: a receiving module and a dispensing module, wherein:
the receiving module is used for receiving a claim request of the use right of the empty resource in the target time period, wherein the empty resource is the resource which is allocated but not used in the target time period;
And the issuing module is used for issuing the use authority of the target time period to the empty resource to a claimant according to the claimant request.
In one embodiment, the issuing module may be used to obtain characteristic data of the claimant; determining the empty resource which is most matched with the claimant in a plurality of empty resources according to the characteristic data; and sending the determined use permission of the empty resource in the target time period to the claimant.
In one embodiment, determining, from the characteristic data, an empty resource of a plurality of empty resources that best matches the claimant may include: and searching for the empty resources which are most matched with the claimant from a shared resource pool, wherein all predicted resources which are allocated but not used in a target time period are stored in the shared resource pool.
In one embodiment, the above-mentioned empty resources may include, but are not limited to, at least one of: a single resource amount of resources, and a resource region containing a plurality of resource amounts.
In one embodiment, the above-mentioned empty resources may include, but are not limited to, at least one of: parking space resources, office space resources, server resources, office equipment resources, and court resources.
According to the resource allocation method provided by the application, the resources in the empty state in the allocated resources in the target time period are predicted and obtained based on the historical empty data of the allocated resources, and then the use rights of the resources are allocated again, so that the technical problem of the existing resource waste is effectively solved, and the technical effect of effectively improving the resource utilization rate is achieved.
The present application also provides a client, as shown in fig. 12, where the client specifically includes: a processor 1202 and a display 1201, which may be connected by an internal bus, for user interaction. Wherein, the display 1201 may be specifically used to display a first interface; the processor 1202 may be specifically configured to receive a resource claim request input by a user at the first interface, where the resource claim request carries a target time period for requesting use, and the claim request is used for requesting a right to use a resource in the allocated resource in an idle state in the target time period; the display 1201 may also be used to display claim results.
Although the application provides method operational steps as described in the examples or flowcharts, more or fewer operational steps may be included based on conventional or non-inventive labor. The order of steps recited in the embodiments is merely one way of performing the order of steps and does not represent a unique order of execution. When implemented by an actual device or client product, the instructions may be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment) as shown in the embodiments or figures.
The apparatus or module set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. For convenience of description, the above devices are described as being functionally divided into various modules, respectively. The functions of the various modules may be implemented in the same piece or pieces of software and/or hardware when implementing the present application. Of course, a module that implements a certain function may be implemented by a plurality of sub-modules or a combination of sub-units.
The methods, apparatus or modules described in the present application may be implemented in computer readable program code means and a controller may be implemented in any suitable manner, for example, the controller may take the form of a microprocessor or processor and a computer readable medium storing computer readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable logic controllers and embedded microcontrollers, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, atmel AT91SAM, microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic of the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller in a pure computer readable program code, it is well possible to implement the same functionality by logically programming the method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. Such a controller can be regarded as a hardware component, and means for implementing various functions included therein can also be regarded as a structure within the hardware component. Or even means for achieving the various functions may be regarded as either software modules implementing the methods or structures within hardware components.
Some of the modules of the apparatus of the present application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, classes, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
From the above description of embodiments, it will be apparent to those skilled in the art that the present application may be implemented in software plus necessary hardware. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product or may be embodied in the implementation of data migration. The computer software product may be stored on a storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., comprising instructions for causing a computer device (which may be a personal computer, mobile terminal, server, or network device, etc.) to perform the methods described in the various embodiments or portions of the embodiments of the application.
Various embodiments in this specification are described in a progressive manner, and identical or similar parts are all provided for each embodiment, each embodiment focusing on differences from other embodiments. All or portions of the present application are operational with numerous general purpose or special purpose computer system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet devices, mobile communication terminals, multiprocessor systems, microprocessor-based systems, programmable electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
Although the present application has been described by way of examples, one of ordinary skill in the art appreciates that there are many variations and modifications that do not depart from the spirit of the application, and it is intended that the appended claims encompass such variations and modifications as fall within the spirit of the application.
Claims (17)
1. A method for resource allocation, comprising:
acquiring historical empty data of the allocated resources; wherein the allocated resources include at least one of: parking space resources, office space resources, server resources, office equipment resources, court resources, meeting room resources, fitness equipment resources and learning resources;
Predicting the resources in the empty state in the allocated resources in the target time period according to the historical empty data; comprising the following steps: training to obtain a blank resource prediction model according to the historical blank data; predicting and obtaining resources in an empty state in the allocated resources in the target time period through the prediction model;
and distributing the predicted use right of the resource in the empty state in the target time period.
2. The method of claim 1, wherein the historical null data comprises at least one of: characteristic data of a resource assigner, blank condition data of an assigned resource and influence factor data of whether the resource can be used.
3. The method of claim 1, wherein the resource in the empty state comprises at least one of: a single resource amount of resources, and a resource region containing a plurality of resource amounts.
4. The method of claim 1, wherein assigning usage rights for the target time period for the predicted resource in the empty state comprises:
and opening the use right in the target time period for the user claiming the use right.
5. The method according to any one of claims 1 to 4, wherein the allocated resources comprise at least one of: parking space resources, office space resources, server resources, office equipment resources, court resources, meeting room resources, fitness equipment resources, and learning resources.
6. A method for resource allocation, comprising:
receiving a claim request of the use right of the empty resource in the target time period, wherein the empty resource is the resource which is allocated but not used in the target time period; the empty resource is determined in the following manner: training to obtain an empty resource prediction model according to the historical empty data; predicting the resources in the empty state in the allocated resources in the target time period through the prediction model; the allocated resources include at least one of: parking space resources, office space resources, server resources, office equipment resources, court resources, meeting room resources, fitness equipment resources and learning resources;
and according to the claim request, issuing the use authority of the target time period to the blank resource to a claimant.
7. The method of claim 6, wherein issuing the usage rights of the empty resource for the target time period to the claimant in accordance with the claim request comprises:
Acquiring characteristic data of a claimant;
determining the empty resource which is most matched with the claimant in a plurality of empty resources according to the characteristic data;
and sending the determined use permission of the empty resource in the target time period to the claimant.
8. The method of claim 7, wherein determining, based on the characteristic data, an empty resource of a plurality of empty resources that best matches the claimant comprises:
and searching for the empty resources which are most matched with the claimant from a shared resource pool, wherein all predicted resources which are allocated but not used in a target time period are stored in the shared resource pool.
9. The method of claim 6, wherein the free resources comprise at least one of: a single resource amount of resources, and a resource region containing a plurality of resource amounts.
10. The method of claim 6, wherein the free resources comprise at least one of: parking space resources, office space resources, server resources, office equipment resources, court resources, meeting room resources, fitness equipment resources, and learning resources.
11. A resource claim method, comprising:
Displaying a first interface;
receiving a resource claim request input by a user on the first interface, wherein the resource claim request carries a target time period for requesting use, and the claim request is used for requesting the use right of the resource in the allocated resource in an empty state in the target time period; the resources in the idle state for the target time period are determined as follows: training to obtain an empty resource prediction model according to the historical empty data; predicting the resources in the empty state in the allocated resources in the target time period through the prediction model; the allocated resources include at least one of: parking space resources, office space resources, server resources, office equipment resources, court resources, meeting room resources, fitness equipment resources and learning resources;
and displaying the claim result.
12. The method of claim 11, wherein the claim result comprises: whether or not the declaration was successful, the reason for the failure, and the resource information of the successful resource.
13. The method of claim 11, wherein after receiving a resource claim request entered by a user at the first interface, the method further comprises:
Displaying a plurality of resources which are in a vacant state in the target time period in the allocated resources;
receiving a selection instruction of a user for the plurality of resources;
and allocating the use right of the resource selected by the selection instruction to the user.
14. A resource allocation server comprising a processor and a memory for storing processor executable instructions which when executed by the processor implement the steps of the method of any one of claims 1 to 5.
15. A resource allocation server comprising a processor and a memory for storing processor executable instructions which when executed by the processor implement the steps of the method of any one of claims 6 to 10.
16. A client, comprising: a processor, and a display, wherein,
the display is used for displaying a first interface;
the processor is used for receiving a resource claim request input by a user at the first interface, wherein the resource claim request carries a target time period for requesting use, and the claim request is used for requesting the use right of the resource in the allocated resource in an empty state in the target time period; the resources in the idle state for the target time period are determined as follows: training to obtain an empty resource prediction model according to the historical empty data; predicting the resources in the empty state in the allocated resources in the target time period through the prediction model; the allocated resources include at least one of: parking space resources, office space resources, server resources, office equipment resources, court resources, meeting room resources, fitness equipment resources and learning resources;
The display is also used for displaying the claim result.
17. A computer readable storage medium having stored thereon computer instructions which when executed implement the steps of the method of any of claims 1 to 5.
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