TY  - GEN
N2  - 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.
DO  - 10.1007/978-981-10-7875-0
DO  - doi
AB  - 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.
T1  - Combustion Optimization Based on Computational Intelligence /
AU  - Zhou, Hao,
AU  - Cen, Kefa,
CN  - TJ254.5
CN  - T58.8
ID  - 826558
KW  - Combustion
KW  - Computational intelligence.
KW  - Chemical engineering.
KW  - Electric power production.
KW  - Thermodynamics.
KW  - Heat engineering.
KW  - Heat
KW  - Mass transfer.
SN  - 9789811078750
SN  - 9811078750
TI  - Combustion Optimization Based on Computational Intelligence /
LK  - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-981-10-7875-0
UR  - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-981-10-7875-0
ER  -