文章基本信息

标题：Monthly Energy Consumption Forecasting Based On Windowed Momentum Neural Network
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作者：Sukumar Mishra ; Vivek Kumar Singh
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2015
卷号：48
期号：30
页码：433-438
DOI：10.1016/j.ifacol.2015.12.417
语种：English
出版社：Elsevier
摘要：AbstractArtificial Neural Network (ANN) with adaptability and non-linearity is well suited to perform forecasting tasks. The paper proposes the systematic approach of monthly energy forecasting using Windowed Momentum Algorithm in ANN. It describes the mathematical foundations and implementation to calculate the monthly energy demand using previous three years consecutive monthly energy data and weather information. The results are compared with the standard momentum, generally used in Back Propagation Algorithm. The proposed algorithm shows good accuracy with maximum mean absolute percentage error of 1.177%.
关键词：KeywordsArtificial Neural NetworkEnergy ForecastingWindowed Momentum