Combustion Optimization Based on Computational Intelligence

• Κύριοι συγγραφείς: Zhou, Hao (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Cen, Kefa (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: Advanced Topics in Science and Technology in China,
• Θέματα: Energy efficiency.; Thermodynamics.; Heat engineering.; Heat transfer.; Mass transfer.; Energy systems.; Chemical engineering.; Computational intelligence.; Energy Efficiency.; Engineering Thermodynamics, Heat and Mass Transfer.; Energy Systems.; Industrial Chemistry/Chemical Engineering.; Computational Intelligence.

 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. 

 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.