Recent metaheuristics algorithms for parameter identification /

Recent metaheuristics algorithms for parameter identification /

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Bibliographic Details
Author / Creator:	Cuevas, Erik, author.
Imprint:	Cham, Switzerland : Springer, [2020]
Description:	1 online resource (xiv, 297 pages.)
Language:	English
Series:	Studies in computational intelligence, 1860-9503 ; volume 854 Studies in computational intelligence ; v. 854.
Subject:	Heuristic algorithms. Metaheuristics. Heuristic algorithms. Metaheuristics.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/12602009

Hidden Bibliographic Details
Other authors / contributors:	Gálvez, Jorge, author. Avalos, Omar, author.
ISBN:	9783030289171 3030289176 9783030289164 3030289168 9783030289164 9783030289188 3030289184 9783030289195 3030289192
Digital file characteristics:	text file PDF
Notes:	Includes bibliographical references. Online resource; title from PDF title page (SpringerLink, viewed September 20, 2019).
Summary:	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.
Other form:	Printed edition: 9783030289164 Printed edition: 9783030289188 Printed edition: 9783030289195
Standard no.:	10.1007/978-3-030-28917-1

Description
Summary:	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.
Physical Description:	1 online resource (xiv, 297 pages.)
Bibliography:	Includes bibliographical references.
ISBN:	9783030289171 3030289176 9783030289164 3030289168 9783030289188 3030289184 9783030289195 3030289192
ISSN:	1860-9503 ;