Combustion Optimization Based on Computational Intelligence / Hao Zhou, Kefa Cen.
2018
TJ254.5 .Z46 2018
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Details
Title
Combustion Optimization Based on Computational Intelligence / Hao Zhou, Kefa Cen.
Author
Zhou, Hao, author.
ISBN
9789811078750 (electronic book)
9811078750 (electronic book)
9789811078736
9811078734
9811078750 (electronic book)
9789811078736
9811078734
Published
Singapore : Springer Singapore ; Hangzhou, China : Zhejiang University Press, [2018]
Language
English
Description
1 online resource (xxvi, 270 pages) : illustrations.
Item Number
10.1007/978-981-10-7875-0 doi
Call Number
TJ254.5 .Z46 2018
Dewey Decimal Classification
621.402/3
658.26
658.26
Summary
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.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Digital File Characteristics
text file PDF
Source of Description
Description based on online resource; title from digital title page (viewed on April 20, 2018).
Added Author
Cen, Kefa, author.
Series
Advanced topics in science and technology in China.
Available in Other Form
Print version: 9789811078736
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Online Access
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Online Resources > Ebooks
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Table of Contents
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.
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.