Optimization of PID Controllers Using Ant Colony and Genetic Algorithms
Artificial neural networks, genetic algorithms and the ant colony optimization algorithm have become a highly effective tool for solving hard optimization problems. As their popularity has increased, applications of these algorithms have grown in more than equal measure. While many of the books avai...
Enregistré dans:
| Auteurs principaux: | , , , |
|---|---|
| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Édition: | 1st ed. 2013. |
| Collection: | Studies in Computational Intelligence
449 |
| Accès en ligne: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Optimization of PID Controllers Using Ant Colony and Genetic Algorithms, Texte imprimé, 9783642328992 • Optimization of PID Controllers Using Ant Colony and Genetic Algorithms, Texte imprimé, 9783642329012 • Optimization of PID Controllers Using Ant Colony and Genetic Algorithms, Texte imprimé, 9783642434778 • Optimization of PID Controllers Using Ant Colony and Genetic Algorithms, Texte imprimé, 9783642328992 |
Table des matières:
- Artificial Neural Networks Genetic Algorithm Ant Colony Optimization (ACO) An Application for Process System Control