Recent Metaheuristics Algorithms for Parameter Identification
Details
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.
Inhalt
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.
Weitere Informationen
- Allgemeine Informationen- GTIN 09783030289164
- Auflage 1st edition 2020
- Sprache Englisch
- Genre Allgemeines & Lexika
- Lesemotiv Verstehen
- Größe H241mm x B160mm x T23mm
- Jahr 2019
- EAN 9783030289164
- Format Fester Einband
- ISBN 3030289168
- Veröffentlichung 20.09.2019
- Titel Recent Metaheuristics Algorithms for Parameter Identification
- Autor Erik Cuevas , Omar Avalos , Jorge Gálvez
- Untertitel Studies in Computational Intelligence 854
- Gewicht 635g
- Herausgeber Springer Nature Switzerland
- Anzahl Seiten 312
 
 
    
