Book-length examination of combustion optimization based on computational intelligence
Presents recent research outcomes in the past ten years, covering from fundamentals to applications
From authors widely recognized as the world-leading researchers in the subject area
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Professor Hao Zhou received his Ph.D. degree from Zhejiang University in 2004. He is currently Deputy Director of State Key Laboratory of Clean Energy Utilization at Zhejiang University and Director of the Zhejiang University - University of Leeds joint research center for sustainable energy. His research interests include combustion optimization, low pollutant combustion technology for utility boilers, and neural network and support vector machine modeling methods. He has published over 20 academic papers and filed 7 patents in the areas of combustion pollutants control and combustion optimization since 2000.
Professor Kefa Cen is a member of the Chinese Academy of Engineering. He received his Ph.D. degree from Moscow Industrial Technology University and has expertise in clean coal combustion and gasification, poly-generation and comprehensive utilization of energy resources, as well as biomass gasification and bio-oil. He is currently Director of the Institute for Thermal Power Engineering at Zhejiang University and Chairman of the Chinese Society of Power Engineering’s International Cooperation & Exchange Committee. He is also Editor-in-Chief of the Journal of Zhejiang University (Engineering Science) and the Journal of Renewable Energy. He has published over 800 academic papers and 15 books.
This book presents the latest findings on the subject of combustion optimization based on computational intelligence. It covers a broad range of topics, including the modeling of coal combustion characteristics based on artificial neural networks and support vector machines. It also describes the optimization of combustion parameters using genetic algorithms or ant colony algorithms, an online coal optimization system, etc. Accordingly, the book offers a unique guide for researchers in the areas of combustion optimization, NOx emission control, energy and power engineering, and chemical engineering.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents the latest findings on the subject of combustion optimization based on computational intelligence. It covers a broad range of topics, including the modeling of coal combustion characteristics based on artificial neural networks and support vector machines. It also describes the optimization of combustion parameters using genetic algorithms or ant colony algorithms, an online coal optimization system, etc. Accordingly, the book offers a unique guide for researchers in the areas of combustion optimization, NOx emission control, energy and power engineering, and chemical engineering. 296 pp. Englisch. Bestandsnummer des Verkäufers 9789811356780
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Taschenbuch. Zustand: Neu. Combustion Optimization Based on Computational Intelligence | Hao Zhou (u. a.) | Taschenbuch | Advanced Topics in Science and Technology in China | xxvi | Englisch | 2018 | Springer | EAN 9789811356780 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Bestandsnummer des Verkäufers 115285177
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Book-length examination of combustion optimization based on computational intelligencePresents recent research outcomes in the past ten years, covering from fundamentals to applicationsFrom authors widely recognized as the world-leading researchers in the subject areaSpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 296 pp. Englisch. Bestandsnummer des Verkäufers 9789811356780
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents the latest findings on the subject of combustion optimization based on computational intelligence. It covers a broad range of topics, including the modeling of coal combustion characteristics based on artificial neural networks and support vector machines. It also describes the optimization of combustion parameters using genetic algorithms or ant colony algorithms, an online coal optimization system, etc. Accordingly, the book offers a unique guide for researchers in the areas of combustion optimization, NOx emission control, energy and power engineering, and chemical engineering. Bestandsnummer des Verkäufers 9789811356780
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