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Title
Recent metaheuristics algorithms for parameter identification / Erik Cuevas, Jorge Gálvez, Omar Avalos.
ISBN
9783030289171 (electronic book)
3030289176 (electronic book)
9783030289164
Published
Cham, Switzerland : Springer, [2020]
Language
English
Description
1 online resource (xiv, 297 pages.)
Other Standard Identifiers
10.1007/978-3-030-28917-1 doi
Call Number
QA76.9.A43
Dewey Decimal Classification
005.1
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.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed September 20, 2019).
Series
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.
