Application of Artificial Neural Network and Pattern Recognition Models for Next Day 24 hours Load Forecasting in Thailand

カテゴリ: 部門大会

論文No: 38

グループ名: 【B】平成21年電気学会電力・エネルギー部門大会講演論文集

発行日: 2009/08/18

タイトル(英語): Application of Artificial Neural Network and Pattern Recognition Models for Next Day 24 hours Load Forecasting in Thailand

著者名: Phatchakorn Areekul(University of the Ryukyus),Tomonobu Senjyu(University of the Ryukyus),Hirofumi Toyama(University of the Ryukyus),Atsushi Yona(University of the Ryukyus)

著者名(英語): Areekul Phatchakorn(University of the Ryukyus),Senjyu Tomonobu(University of the Ryukyus),Toyama Hirofumi(University of the Ryukyus),Yona Atsushi(University of the Ryukyus)

キーワード: Short-term load forecasting|artificial neural network|pattern recognition|back-propagation|Short-term load forecasting|artificial neural network|pattern recognition|back-propagation

要約(日本語): Short term load forecasting (STLF) plays an important role in operation planning, control and interchange transaction scheduling for great saving in electric utility organizations. Most traditional forecasting models and Artificial Neural Network (ANN) te

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