Recent Metaheuristics Algorithms for Parameter Identification (Hardcover)

Erik Cuevas

ISBN 10: 3030289168 / ISBN 13: 9783030289164

Published by Springer Nature Switzerland AG, Cham, 2019

About this Item

Hardcover. This book presents new, alternative metaheuristic developments that have proved to be effective in various complex problems to help researchers, lecturers, engineers, and practitioners solve their own optimization problems. It also bridges the gap between recent metaheuristic techniques and interesting identification system methods that benefit from the convenience of metaheuristic schemes by explaining basic ideas of the proposed applications in ways that can be understood by readers new to these fields. As such it is a valuable resource for energy practitioners who are not researchers in metaheuristics. In addition, it offers members of the metaheuristic community insights into how system identification and energy problems can be translated into optimization tasks. This book presents new, alternative metaheuristic developments that have proved to be effective in various complex problems to help researchers, lecturers, engineers, and practitioners solve their own optimization problems. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Seller Inventory # 9783030289164

Bibliographic Details

• Title: Recent Metaheuristics Algorithms for Parameter Identification (Hardcover)
• Publisher: Springer Nature Switzerland AG, Cham
• Publication Date: 2019
• Language: English
• ISBN 10: 3030289168
• ISBN 13: 9783030289164
• Binding: Hardcover
• Condition: new

About this title

Synopsis

This book presents new, alternative metaheuristic developments that have proved to be effective in various complex problems to help researchers, lecturers, engineers, and practitioners solve their own optimization problems. It also bridges the gap between recent metaheuristic techniques and interesting identification system methods that benefit from the convenience of metaheuristic schemes by explaining basic ideas of the proposed applications in ways that can be understood by readers new to these fields. As such it is a valuable resource for energy practitioners who are not researchers in metaheuristics. In addition, it offers members of the metaheuristic community insights into how system identification and energy problems can be translated into optimization tasks.