Multi Objective Optimization Of Industrial Power Generation Systems Emerging Research And Opportunities

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Multi-Objective Optimization of Industrial Power Generation Systems: Emerging Research and Opportunities

Multi-Objective Optimization of Industrial Power Generation Systems: Emerging Research and Opportunities
Author :
Publisher : IGI Global
Total Pages : 233
Release :
ISBN-10 : 9781799817123
ISBN-13 : 1799817121
Rating : 4/5 (121 Downloads)

Book Synopsis Multi-Objective Optimization of Industrial Power Generation Systems: Emerging Research and Opportunities by : Ganesan, Timothy

Download or read book Multi-Objective Optimization of Industrial Power Generation Systems: Emerging Research and Opportunities written by Ganesan, Timothy and published by IGI Global. This book was released on 2019-12-27 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increased complexity of the economy in recent years has led to the advancement of energy generation systems. Engineers in this industrial sector have been compelled to seek contemporary methods to keep pace with the rapid development of these systems. Computational intelligence has risen as a capable method that can effectively resolve complex scenarios within the power generation sector. In-depth research on the various applications of this technology is lacking, as engineering professionals need up-to-date information on how to successfully utilize computational intelligence in industrial systems. Multi-Objective Optimization of Industrial Power Generation Systems: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of the application of intelligent optimization techniques within industrial energy systems. Featuring coverage on a broad range of topics such as swarm intelligence, renewable energy, and predictive modeling, this book is ideally designed for industrialists, engineers, industry professionals, researchers, students, and academics seeking current research on computational intelligence frameworks within the power generation sector.


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