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Reconstruction and intelligent contr...

Peng, Chen.

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Reconstruction and intelligent control for power plant

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Reconstruction and intelligent control for power plant/ by Chen Peng, Chuanliang Cheng, Ling Wang.
作者:	Peng, Chen.
其他作者:	Cheng, Chuanliang.
出版者:	Singapore :Springer Nature Singapore : : 2023.,
面頁冊數:	xv, 208 p. :ill. (chiefly color), digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Intelligent control systems. -
電子資源:	https://doi.org/10.1007/978-981-19-5574-7
ISBN:	9789811955747

Reconstruction and intelligent control for power plant
Peng, Chen.

Reconstruction and intelligent control for power plant[electronic resource] /by Chen Peng, Chuanliang Cheng, Ling Wang. - Singapore :Springer Nature Singapore :2023. - xv, 208 p. :ill. (chiefly color), digital ;24 cm.

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.

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.

ISBN: 9789811955747

Standard No.: 10.1007/978-981-19-5574-7doiSubjects--Topical Terms:

546464
Intelligent control systems.

LC Class. No.: TJ217.5

Dewey Class. No.: 629.89563

Reconstruction and intelligent control for power plant
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505 0 $a 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.
520 $a 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.
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