Advanced Methods of Power Load Forecasting

This reprint introduces advanced prediction models focused on power load forecasting. Models based on artificial intelligence and more traditional approaches are shown, demonstrating the real possibilities of use to improve prediction in this field. Models of LSTM neural networks, LSTM networks with...

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書誌詳細
フォーマット:	Online
言語:	英語
出版事項:	MDPI - Multidisciplinary Digital Publishing Institute 2022
主題:	Prophet model Holt–Winters model long-term forecasting peak load prophet model multiple seasonality time series demand load forecast DIMS irregular galvanizing short-term electrical load forecasting machine learning deep learning statistical analysis parameters tuning CNN LSTM short-term load forecast Artificial Neural Network deep neural network recurrent neural network attention encoder decoder online training bidirectional long short-term memory multi-layer stacked neural network short-term load forecasting power system thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science::PH Physics
オンライン･アクセス:	ONIX_20220621_9783036542188_83
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ONIX_20220621_9783036542188_83

Advanced Methods of Power Load Forecasting

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