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Feb 3, 2024 · This work performs a study exploring clustering methods in a trucks data set of logged inclinations on the roadway, a Big Data problem. With a ...
With a good clustering, the data becomes key to improve product development and fuel efficiency, since different environment of truck usage can be identified.
With a good clustering, the data becomes key to improve product development and fuel efficiency, since different environment of truck usage can be identified.
SEIXAS, Lenon Diniz. Vehicle industry big data analysis using clustering approaches. 2022. Dissertação (Mestrado em Engenharia Elétrica) - Universidade ...
This paper considers an approach to clustering of time series data using automatically extracted features in the domain of vehicle telematics data analysis and ...
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Cluster Analysis in Machine Learning: A Case Study | Medium
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Feb 8, 2024 · Clustering is a technique in machine learning and data analysis that involves grouping similar data points based on certain features or characteristics.
Sep 15, 2022 · We provide a method for extracting driving episodes from data utilizing clustering algorithms. This method starts with clustering driving data.
This way, clustering techniques are used to identify pricing anomalies in similar parts, using their specifications as a basis.
Nov 1, 2023 · A big data-driven correlation analysis based on clustering is proposed to improve energy and resource utilisation efficiency in this paper.
Jan 17, 2023 · This paper summarizes the principles, advantages, and disadvantages of 20 traditional clustering algorithms and 4 modern algorithms.