Linda Faridah, M. A. Risnandar, Imam Taufiqurrahman, A. Rahayu
{"title":"APLIKASI ALGORITMA FEED FORWARD BACKPROPAGATION UNTUK BEBAN LISTRIK HARI LIBUR PADA TIPE BEBAN ANOMALI","authors":"Linda Faridah, M. A. Risnandar, Imam Taufiqurrahman, A. Rahayu","doi":"10.37058/jeee.v2i1.2123","DOIUrl":null,"url":null,"abstract":"Load pattern for holiday have significant differenct from weekday day, so that require special prediction. This research have purpose to test the performance feed forward backpropagation to know accuracy level of load forecasting for holiday anomalous load. Learning algorithm used feed forward backpropagation from artificial neural network with matlab. Load forecasting optimization is change learning rate and some of learning input. The reasult of this reasult showed learning input give best reasult on mean but difference from that value is small, so learning rate variation small affected at learning","PeriodicalId":341918,"journal":{"name":"Journal of Energy and Electrical Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Energy and Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37058/jeee.v2i1.2123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Load pattern for holiday have significant differenct from weekday day, so that require special prediction. This research have purpose to test the performance feed forward backpropagation to know accuracy level of load forecasting for holiday anomalous load. Learning algorithm used feed forward backpropagation from artificial neural network with matlab. Load forecasting optimization is change learning rate and some of learning input. The reasult of this reasult showed learning input give best reasult on mean but difference from that value is small, so learning rate variation small affected at learning