Integrated profile of EV user behavior and value based on charging data mining

Bin Zhu; Wen Hu; Dong Yan; Chong-Yang Luo; Chuang-Liang Zhao

doi:10.1117/12.2689491

10 August 2023 Integrated profile of EV user behavior and value based on charging data mining

Bin Zhu, Wen Hu, Dong Yan, Chong-Yang Luo, Chuang-Liang Zhao

Proceedings Volume 12748, 5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023); 1274814 (2023) https://doi.org/10.1117/12.2689491
Event: 5th International Conference on Information Science, Electrical and Automation Engineering (ISEAE 2023), 2023, Wuhan, China

Abstract

This study propose an integrated user behavior and value profiling method, which aims to build a more comprehensive index system to evaluate user value and demand. This method mainly includes a Time-Decay-Based Label Matching (TDBLM) method and an extended RFM model. The TDBLM method can effectively deal with the multi-label problem of user charging records due to clustering, and can derive a unique label that can better characterize the current state of users; the extended RFM model is used for user value profiles, and the experimental results show that user value profiles are defined into four categories: Lost, Potential, Retention, and High-value. In order to evaluate the performance of K-means++ used in this method, its performance was compared with that of GMM and Mean Shift clustering methods, and the results showed that the clustering results of K-means++ have better stability and are more suitable for user profiling. Finally, this study also proposes a method to visualize user profiles and make the profile results as knowledge graphs to realize the visualization and fast retrieval of profiles and expand the profile function.

Citation Download Citation

Bin Zhu, Wen Hu, Dong Yan, Chong-Yang Luo, and Chuang-Liang Zhao "Integrated profile of EV user behavior and value based on charging data mining", Proc. SPIE 12748, 5th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2023), 1274814 (10 August 2023); https://doi.org/10.1117/12.2689491

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KEYWORDS

Visualization

Data analysis

Data mining

Data modeling

Profiling

Feature extraction

Statistical analysis

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