Combustion Optimization Based on Computational Intelligence (Advanced Topics in Science and Technology in China) - Softcover

Zhou, Hao; Cen, Kefa

Softcover

ISBN 10: 9811356785 ISBN 13: 9789811356780

Publisher: Springer, 2018

Synopsis

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

About this title

About the Author

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.

From the Back Cover

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.

Edition details

• Publisher: Springer
• Publication date: 2018
• ISBN 10: 9811356785
• ISBN 13: 9789811356780
• Binding: Paperback
• Language: English
• Number of pages: 296