{"title":"基于人工神经网络的中期电力负荷预测","authors":"L. Varga","doi":"10.1109/PTC.1999.826468","DOIUrl":null,"url":null,"abstract":"In the paper artificial neural networks are applied to medium term electric load forecasting for the Hungarian Electric Power System. A feedforward multi-layer network with one hidden layer was applied using the error backpropagation algorithm for the estimation of the model weights. A model description and detailed prediction error analysis are presented.","PeriodicalId":101688,"journal":{"name":"PowerTech Budapest 99. Abstract Records. (Cat. No.99EX376)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Medium term electric load forecasting using artificial neural networks\",\"authors\":\"L. Varga\",\"doi\":\"10.1109/PTC.1999.826468\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the paper artificial neural networks are applied to medium term electric load forecasting for the Hungarian Electric Power System. A feedforward multi-layer network with one hidden layer was applied using the error backpropagation algorithm for the estimation of the model weights. A model description and detailed prediction error analysis are presented.\",\"PeriodicalId\":101688,\"journal\":{\"name\":\"PowerTech Budapest 99. Abstract Records. (Cat. No.99EX376)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"PowerTech Budapest 99. Abstract Records. (Cat. No.99EX376)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PTC.1999.826468\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"PowerTech Budapest 99. Abstract Records. (Cat. No.99EX376)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PTC.1999.826468","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Medium term electric load forecasting using artificial neural networks
In the paper artificial neural networks are applied to medium term electric load forecasting for the Hungarian Electric Power System. A feedforward multi-layer network with one hidden layer was applied using the error backpropagation algorithm for the estimation of the model weights. A model description and detailed prediction error analysis are presented.
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