カテゴリ: 論文誌(論文単位)グループ名: 【B】電力・エネルギー部門発行日: 2024/12/01タイトル(英語): Short-Term Ensemble Insolation Forecasting Method using Parallelized NE著者名: 川﨑 章司（明治大学理工学部電気電子生命学科），石部 晃史（明治大学理工学研究科電気工学専攻）著者名(英語): Shoji Kawasaki (Department of Electoronics and Bioinformatics, School of Science and Technology, Meiji University), Koshi Ishibe (Department of Electrical Enginnering, Graduate School of Science and Technology, Meiji University)キーワード: 日射量予測，ニューロエボリューション，アンサンブル予測，遺伝的アルゴリズム，並列処理 insolation forecasting，neuro evolution，ensemble forecasting，genetic algorithm，parallel processing要約(英語): In this paper, the authors propose an ensemble forecasting method using multiple individuals for short-time-ahead (one hour ahead) insolation forecasting by using neuro evolution (NE), in which a genetic algorithm is applied to the learning algorithm of a neural network for insolation. Although the method improves the accuracy compared to a single forecast, NE has a problem that the training time is long. In order to solve this problem, the authors propose a parallelization method of GPU processing for short-time-ahead forecasting and try to solve the problem by parallelizing the GPU.本誌: 電気学会論文誌B（電力・エネルギー部門誌） Vol.144 No.12 （2024）本誌掲載ページ: 608-615 p原稿種別: 論文／日本語電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejpes/144/12/144_608/_article/-char/ja/
