Issue |
SHS Web Conf.
Volume 219, 2025
2025 International Conference on Management and Intelligent Society Development (MISD2025)
|
|
---|---|---|
Article Number | 02003 | |
Number of page(s) | 5 | |
Section | Intelligent Technology Application | |
DOI | https://doi.org/10.1051/shsconf/202521902003 | |
Published online | 04 July 2025 |
Classification Method For User Electricity Consumption Behavior Based on Power Big Data
School of Information, Shenyang Institute of Engineering, Shenyang, Liaoning, China
* Corresponding author: yushun@sie.edu.cn
According to the insufficiency of existing methods of classification on the behavior of using electricity, this paper proposes a classification method for behavior of user using electricity based on deep convolutional neural networks(DCNN). The method which we proposed can classify the behavior of using electricity, then can support efficiency data for management and optimization of power system. This paper implemented classification mainly on user portrait and the big data of power, based on modeling the electricity using of users’, we used deep convolutional neural networks as our fundamental classification method, and made several improvements in connection with the model of using electricity we had built. The experiments shows that the accuracy of classification method which we proposed could reach 90% and more as a whole, which verified the effectiveness and feasibility of the model and method , and this result can also provide references for the distribution adjustment of our existing power system.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.