| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNINA9910484200003321 |
|
|
Autore |
Cuevas Erik |
|
|
Titolo |
Recent Metaheuristics Algorithms for Parameter Identification / / by Erik Cuevas, Jorge Gálvez, Omar Avalos |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
|
|
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Edizione |
[1st ed. 2020.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (XIV, 297 p.) |
|
|
|
|
|
|
Collana |
|
Studies in Computational Intelligence, , 1860-9503 ; ; 854 |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
|
|
Soggetti |
|
Computational intelligence |
Artificial intelligence |
Computational Intelligence |
Artificial Intelligence |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Nota di contenuto |
|
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. |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
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. |
|
|
|
|
|
| |