{"title":"基于混沌理论和RBF神经网络的短期负荷预测","authors":"Zhenzhen Yuan, Shuang Liu, Linyan Xue, Xiu-e Yuan","doi":"10.1109/ICNC.2011.6022118","DOIUrl":null,"url":null,"abstract":"Power system load is a nonlinear time series, for the complexity and nonlinear of power systems loads, this paper combines the idea of chaos theory, make full use of data in the reconstruction phase space power load based on the load of forecast, due to the approximation capability of neural networks with superior predictive ability, the use of RBF neural network-based method and Matlab simulation, the simulation shows that such a prediction algorithm to obtain good results.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"25 1","pages":"526-529"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Short-term load forecasting based on chaos theory and RBF neural network\",\"authors\":\"Zhenzhen Yuan, Shuang Liu, Linyan Xue, Xiu-e Yuan\",\"doi\":\"10.1109/ICNC.2011.6022118\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Power system load is a nonlinear time series, for the complexity and nonlinear of power systems loads, this paper combines the idea of chaos theory, make full use of data in the reconstruction phase space power load based on the load of forecast, due to the approximation capability of neural networks with superior predictive ability, the use of RBF neural network-based method and Matlab simulation, the simulation shows that such a prediction algorithm to obtain good results.\",\"PeriodicalId\":87274,\"journal\":{\"name\":\"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications\",\"volume\":\"25 1\",\"pages\":\"526-529\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNC.2011.6022118\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2011.6022118","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Short-term load forecasting based on chaos theory and RBF neural network
Power system load is a nonlinear time series, for the complexity and nonlinear of power systems loads, this paper combines the idea of chaos theory, make full use of data in the reconstruction phase space power load based on the load of forecast, due to the approximation capability of neural networks with superior predictive ability, the use of RBF neural network-based method and Matlab simulation, the simulation shows that such a prediction algorithm to obtain good results.