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| Artikel-Nr.: 5667A-9783031453564 Herst.-Nr.: 9783031453564 EAN/GTIN: 9783031453564 |
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 | This book provides readers with an in-depth review of deep learning-based techniques and discusses how they can benefit power system applications. Representative case studies of deep learning techniques in power systems are investigated and discussed, including convolutional neural networks (CNN) for power system security screening and cascading failure assessment, deep neural networks (DNN) for demand response management, and deep reinforcement learning (deep RL) for heating, ventilation, and air conditioning (HVAC) control. is an ideal resource for professors, students, and industrial and government researchers in power systems, as well as practicing engineers and AI researchers. Weitere Informationen:  |  | Author: | Fangxing Li; Yan Du | Verlag: | Springer International Publishing | Sprache: | eng |
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 | Weitere Suchbegriffe: allgemeine technikbücher - englischsprachig, Deep learning, Deep neural network, Convolutional neural network, Deep reinforcement learning, Deep deterministic policy gradient, AlphaGo, Power systems, Security screening, Cascading failure, Demand response, Microgrid |
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