Data Mining and Analysis of New Energy Vehicles Based on Cluster Analysis Technology

Zhengmi Wang

2025

Abstract

Under the trend of social energy gradually moving towards clean energy, the scale of new energy vehicles has gradually increased. The use and production of new energy vehicles generates a large amount of data, such as the status of batteries and motors. Therefore, the role of data mining in the data collection and in-depth analysis of new energy vehicles is very important. However, there is a problem of inaccurate data collection, and the improvement of the battery and power output are unreasonable. Therefore, this paper proposes a cluster analysis technique to perform extensive data mining analysis. Firstly, the data preprocessing and cluster analysis in data mining are used to collect and sort out the data with poor data integrity, and the unified data with strong integrity is obtained for comprehensive analysis. Under the condition that the data evaluation criteria are fixed, the data mining accuracy and response speed of cluster analysis technology to

Paper Citation

in Harvard Style

Wang Z. (2025). Data Mining and Analysis of New Energy Vehicles Based on Cluster Analysis Technology. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 300-306. DOI: 10.5220/0013540300004664

in Bibtex Style

@conference{incoft25,
author={Zhengmi Wang},
title={Data Mining and Analysis of New Energy Vehicles Based on Cluster Analysis Technology},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT},
year={2025},
pages={300-306},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013540300004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT
TI - Data Mining and Analysis of New Energy Vehicles Based on Cluster Analysis Technology
SN - 978-989-758-763-4
AU - Wang Z.
PY - 2025
SP - 300
EP - 306
DO - 10.5220/0013540300004664
PB - SciTePress