4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022)最新文献

Harmonic reduction for permanent magnet synchronous motor sensorless drives 永磁同步电机无传感器驱动的谐波降低

4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022) Pub Date : 2022-08-01 DOI: 10.1117/12.2640358

Xu Zhijie, Yang Kai, Zheng Yifei, Huang Yuhao

引用次数: 0

Electric vehicle load forecasting based on improved neural network based on differential evolution algorithm 基于改进神经网络差分进化算法的电动汽车负荷预测

4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022) Pub Date : 2022-08-01 DOI: 10.1117/12.2640366

Zhu Shiwei, Wu Wenzhen, Zhang Jiahao, Li Na

{"title":"Electric vehicle load forecasting based on improved neural network based on differential evolution algorithm","authors":"Zhu Shiwei, Wu Wenzhen, Zhang Jiahao, Li Na","doi":"10.1117/12.2640366","DOIUrl":"https://doi.org/10.1117/12.2640366","url":null,"abstract":"Under the environment of energy crisis and green development, the development of electric vehicles has become inevitable. However, the charging load of electric vehicles has great uncertainty, which will have a certain impact on the security and stability of the power grid. Accurately predicting the charging load of electric vehicles is an effective method to avoid this problem. Considering the spatiotemporal characteristics of electric vehicle charging load, an electric vehicle load prediction method based on differential evolution algorithm improved BP neural network is proposed to complete the search of the weight space and network structure space of the neural network at the same time. The optimal network structure. The algorithm adopts the (1+1)-ES binary evolution strategy, uses a new network structure crossover and mutation method, and speeds up the search of the neural network model and the algorithm through the co-evolution of dual population structure and adaptive mutation rate strategies. Convergence improves the learning ability of the network and reduces the prediction error of the BP neural network model. The model and the BP neural network model are respectively used to predict the load of electric vehicles, and the comparison results prove the superiority of the proposed model.","PeriodicalId":240234,"journal":{"name":"4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124385047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Front Matter: Volume 12257 封面:第12257卷

4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022) Pub Date : 2022-08-01 DOI: 10.1117/12.2651183

Iseae, Lidan Wang, Mengyi Cen

引用次数: 0

Visual analysis of bus flow based on grid clustering 基于网格聚类的公交流可视化分析

4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022) Pub Date : 2022-08-01 DOI: 10.1117/12.2640174

Pan Xiuqin, Hou Fei

引用次数: 0