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Recent metaheuristics algorithms for...

Cuevas, Erik.

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Recent metaheuristics algorithms for parameter identification

Record Type:	Electronic resources : Monograph/item
Title/Author:	Recent metaheuristics algorithms for parameter identification/ by Erik Cuevas, Jorge Galvez, Omar Avalos.
Author:	Cuevas, Erik.
other author:	Galvez, Jorge.
Published:	Cham :Springer International Publishing : : 2020.,
Description:	xiv, 297 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction to optimization and metaheuristic methods -- Optimization techniques in parameters setting for Induction Motor -- An enhanced crow search algorithm applied to energy approaches -- Comparison of solar cells parameters estimation using several optimization algorithms -- Gravitational search algorithm for non-linear system identification using ANFIS-Hammerstein approach -- Fuzzy Logic Based Optimization Algorithm -- Neighborhood Based Optimization Algorithm -- Knowledge-Based Optimization Algorithm.
Contained By:	Springer Nature eBook
Subject:	Heuristic algorithms. -
Online resource:	https://doi.org/10.1007/978-3-030-28917-1
ISBN:	9783030289171

Recent metaheuristics algorithms for parameter identification
Cuevas, Erik.

Recent metaheuristics algorithms for parameter identification[electronic resource] /by Erik Cuevas, Jorge Galvez, Omar Avalos. - Cham :Springer International Publishing :2020. - xiv, 297 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.8541860-949X ;. - Studies in computational intelligence ;v.854..

Introduction to optimization and metaheuristic methods -- Optimization techniques in parameters setting for Induction Motor -- An enhanced crow search algorithm applied to energy approaches -- Comparison of solar cells parameters estimation using several optimization algorithms -- Gravitational search algorithm for non-linear system identification using ANFIS-Hammerstein approach -- Fuzzy Logic Based Optimization Algorithm -- Neighborhood Based Optimization Algorithm -- Knowledge-Based Optimization Algorithm.

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.

ISBN: 9783030289171

Standard No.: 10.1007/978-3-030-28917-1doiSubjects--Topical Terms:

1066682
Heuristic algorithms.

LC Class. No.: QA76.9.A43 / C84 2020

Dewey Class. No.: 005.1

Recent metaheuristics algorithms for parameter identification
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245 1 0 $a Recent metaheuristics algorithms for parameter identification $h [electronic resource] / $c by Erik Cuevas, Jorge Galvez, Omar Avalos.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xiv, 297 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v v.854
505 0 $a Introduction to optimization and metaheuristic methods -- Optimization techniques in parameters setting for Induction Motor -- An enhanced crow search algorithm applied to energy approaches -- Comparison of solar cells parameters estimation using several optimization algorithms -- Gravitational search algorithm for non-linear system identification using ANFIS-Hammerstein approach -- Fuzzy Logic Based Optimization Algorithm -- Neighborhood Based Optimization Algorithm -- Knowledge-Based Optimization Algorithm.
520 $a 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.
650 0 $a Heuristic algorithms. $3 1066682
650 0 $a Metaheuristics. $3 2206834
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence. $3 769149
700 1 $a Galvez, Jorge. $3 3530238
700 1 $a Avalos, Omar. $3 3530239
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Studies in computational intelligence ; $v v.854. $3 3530240
856 4 0 $u https://doi.org/10.1007/978-3-030-28917-1
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)