An experimental approach to design deterministic and adaptive control schemes for grouping genetic algorithms

Genetic algorithms can solve many complex problems, including designing and optimizing machine learning techniques like neural networks, as well as challenges in production management and engineering. Paradoxically, the design of these methods, which aim to solve optimization problems efficiently, d...

Full description

Saved in:

Bibliographic Details
Published in:	Neural computing & applications Vol. 37; no. 33; pp. 27811 - 27840
Main Authors:	Flores-Torres, Leonardo, Quiroz-Castellanos, Marcela, Ramos-Figueroa, Octavio, Amador-Larrea, Stephanie
Format:	Journal Article
Language:	English
Published:	London Springer London 01.11.2025 Springer Nature B.V
Subjects:	Adaptive control Artificial Intelligence Combinatorial analysis Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Configuration management Data Mining and Knowledge Discovery Design Exploitation Genetic algorithms Heuristic methods Image Processing and Computer Vision Machine learning Mutation Neural networks Optimization Parameter identification Probability and Statistics in Computer Science Production management S.I.: 2023 India International Congress on Computational Intelligence Solution space Space exploration Special Issue on 2023 India International Congress on Computational Intelligence Grouping genetic algorithm Parameter setting Parameter control Adaptive control Deterministic control
ISSN:	0941-0643, 1433-3058
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!