Academic Journal of Engineering and Technology Science, 2022, 5(4); doi: 10.25236/AJETS.2022.050403.
Lin Mei1, Fengdai Kang2
1Department of Basic Education, Shandong University of Engineering and Vocational Technology, Jinan, 250200, China
2Department of Liberal Arts (Career-Oriented Multidisciplinary Education Center), Shenzhen Institute of Information Technology, Shenzhen, 518172, China
With the rise of new energy vehicles, the coverage of charging piles is becoming more and more extensive, so it is necessary to study the charging demand. In this paper, a charging demand prediction model is constructed by using the BP neural network based on the whale optimization algorithm, and an empirical study is carried out by taking a charging pile in Shanghai as an example. The research results show that the MAPE of the WOA-BP neural network is about 7.65% lower than that of the BP neural network, which shows that WOA-BPNN model is more suitable for the prediction of charging demand and its prediction results can provide a certain decision-making basis for the allocation and deployment of charging piles in the future.
WOA-BP neural network; charge amount; prediction
Lin Mei, Fengdai Kang. Research on Prediction Model of Daily Charging Demand Based on WOA-BP. Academic Journal of Engineering and Technology Science (2022) Vol. 5, Issue 4: 13-17. https://doi.org/10.25236/AJETS.2022.050403.
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