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Reconstruction and Intelligent Control for Power Plant / by Chen Peng, Chuanliang Cheng, Ling Wang

By: Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Publisher: Singapore : Springer Nature Singapore, 2023Publisher: Singapore : Imprint: Springer, 2023Edition: 1st ed. 2023Description: 1 Online-Ressource(XV, 208 p. 100 illus., 90 illus. in color.)ISBN:
  • 9789811955747
Subject(s): Additional physical formats: 9789811955730 | 9789811955754 | 9789811955761 | Erscheint auch als: 9789811955730 Druck-Ausgabe | Erscheint auch als: 9789811955754 Druck-Ausgabe | Erscheint auch als: 9789811955761 Druck-AusgabeDOI: DOI: 10.1007/978-981-19-5574-7Online resources: Summary: Introduction -- Adaptive mixed edge detection of furnace flame image -- Intelligent flame image segmentation of furnace flame image -- Reconstruction of temperature field based on limited flame image information -- Furnace temperature prediction based on optimized kernel extreme learning machine -- Process modeling of power plant -- Fuzzy K-means network based generalized predictive control for power plant -- Deep-neural-network based nonlinear predictive control for power plant -- Intelligent virtual reference feedback tuning based data driven control for power plant.Summary: The authors' innovative research ideas in power plant control are presented in this book. This book focuses on 1) cognition and reconstruction of the temperature field; 2) intelligent setting and learning of power plants; 3) energy efficiency optimization and intelligent control for power plants, and so on, using historical power plant operation data and creative methods such as reconstruction of the combustion field, deep reinforcement learning, and networked collaborative control. It could help researchers, industrial engineers, and graduate students in the areas of signal detection, image processing, and control engineering.PPN: PPN: 1817572237Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-INR | ZDB-2-SXIT
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