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Author Zhou, Hao, author
Title Combustion Optimization Based on Computational Intelligence / by Hao Zhou, Kefa Cen
Imprint Singapore : Springer Singapore : Imprint: Springer, 2018
book jacket
Descript 1 online resource (xxvi, 270 pages) : illustrations (some color), digital ; 24 cm
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
text file PDF rda
Series Advanced topics in science and technology in China, 1995-6819
Advanced topics in science and technology in China
Note The influence of combustion parameters on NOx emissions and carbon burnout -- Modeling methods for combustion characteristics -- Neural network modeling of combustion characteristics -- Support vector machine modeling the combustion characteristics -- Combining neural network or support vector machine with optimization algorithms to optimize the combustion -- Online combustion optimization system
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
Host Item Springer eBooks
Subject Combustion -- Mathematical models
Computational intelligence
Energy
Energy Efficiency
Engineering Thermodynamics, Heat and Mass Transfer
Energy Technology
Industrial Chemistry/Chemical Engineering
Computational Intelligence
Alt Author Cen, Kefa, author
SpringerLink (Online service)
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