具有专门结构的前馈神经网络用于估计温度对电力负荷的影响

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI:10.1109/IS.2008.4670444

Y. Bodyanskiy, S. Popov, T. Rybalchenko

{"title":"具有专门结构的前馈神经网络用于估计温度对电力负荷的影响","authors":"Y. Bodyanskiy, S. Popov, T. Rybalchenko","doi":"10.1109/IS.2008.4670444","DOIUrl":null,"url":null,"abstract":"The problem of temperature-load relationship revealing is considered. A specialized architecture of a feedforward neural network is proposed that provides separation of temperature influence from other factors and its analysis in an explicit form. The proposed approach is illustrated by computational experiments with data from two locations with different climatic conditions.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Feedforward neural network with a specialized architecture for estimation of the temperature influence on the electric load\",\"authors\":\"Y. Bodyanskiy, S. Popov, T. Rybalchenko\",\"doi\":\"10.1109/IS.2008.4670444\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The problem of temperature-load relationship revealing is considered. A specialized architecture of a feedforward neural network is proposed that provides separation of temperature influence from other factors and its analysis in an explicit form. The proposed approach is illustrated by computational experiments with data from two locations with different climatic conditions.\",\"PeriodicalId\":305750,\"journal\":{\"name\":\"2008 4th International IEEE Conference Intelligent Systems\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 4th International IEEE Conference Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IS.2008.4670444\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 4th International IEEE Conference Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IS.2008.4670444","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 4

摘要

考虑了温度-载荷关系揭示问题。提出了一种特殊的前馈神经网络结构，将温度影响与其他因素分离并以显式形式进行分析。用两个不同气候条件下的数据进行了计算实验，验证了该方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Feedforward neural network with a specialized architecture for estimation of the temperature influence on the electric load

The problem of temperature-load relationship revealing is considered. A specialized architecture of a feedforward neural network is proposed that provides separation of temperature influence from other factors and its analysis in an explicit form. The proposed approach is illustrated by computational experiments with data from two locations with different climatic conditions.

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

2008 4th International IEEE Conference Intelligent Systems

自引率

0.00%

发文量