基于回波状态神经网络的地铁供电系统短期负荷预测模型

Yu Litao, Han Aoyang, Wang Li, Jia Xu, Zhang Zhisheng
{"title":"基于回波状态神经网络的地铁供电系统短期负荷预测模型","authors":"Yu Litao, Han Aoyang, Wang Li, Jia Xu, Zhang Zhisheng","doi":"10.1109/ICSESS.2016.7883212","DOIUrl":null,"url":null,"abstract":"The paper presents a short-term load forecasting model for metro power supply system based on echo state neural network. Echo state neural network composed of input layer, reserve pool, the output layer. Reserve pool as a dynamic network is connected by a large number of random sparse of neurons. Reserve pool is used to overcome the slow convergence speed and avoid neural network into the local minimum. Using the actual historical data of the metro power supply system to simulate, the simulation results show that the short-term load forecasting model for metro power supply system based on echo state neural network has good prediction accuracy.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Short-term load forecasting model for metro power supply system based on echo state neural network\",\"authors\":\"Yu Litao, Han Aoyang, Wang Li, Jia Xu, Zhang Zhisheng\",\"doi\":\"10.1109/ICSESS.2016.7883212\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a short-term load forecasting model for metro power supply system based on echo state neural network. Echo state neural network composed of input layer, reserve pool, the output layer. Reserve pool as a dynamic network is connected by a large number of random sparse of neurons. Reserve pool is used to overcome the slow convergence speed and avoid neural network into the local minimum. Using the actual historical data of the metro power supply system to simulate, the simulation results show that the short-term load forecasting model for metro power supply system based on echo state neural network has good prediction accuracy.\",\"PeriodicalId\":175933,\"journal\":{\"name\":\"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSESS.2016.7883212\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSESS.2016.7883212","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

提出了一种基于回波状态神经网络的地铁供电系统短期负荷预测模型。回声状态神经网络由输入层、储备池、输出层组成。储备池作为一个动态网络,由大量随机稀疏的神经元连接而成。利用储备池克服了收敛速度慢的问题,避免了神经网络陷入局部极小值。利用地铁供电系统的实际历史数据进行仿真,仿真结果表明,基于回波状态神经网络的地铁供电系统短期负荷预测模型具有较好的预测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Short-term load forecasting model for metro power supply system based on echo state neural network
The paper presents a short-term load forecasting model for metro power supply system based on echo state neural network. Echo state neural network composed of input layer, reserve pool, the output layer. Reserve pool as a dynamic network is connected by a large number of random sparse of neurons. Reserve pool is used to overcome the slow convergence speed and avoid neural network into the local minimum. Using the actual historical data of the metro power supply system to simulate, the simulation results show that the short-term load forecasting model for metro power supply system based on echo state neural network has good prediction accuracy.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信