Soft computing for control of non-linear dynamical systems
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This book explores the application of soft computing techniques to the modeling, simulation, prediction, and control of nonlinear dynamical systems. It focuses on fuzzy logic, artificial neural networks, genetic algorithms, simulated annealing, chaos theory, and hybrid intelligent systems. The authors explain how these techniques can be combined to develop intelligent control systems capable of handling complex nonlinear behavior, adapting to changing conditions, and optimizing system performance. Applications include robotics, biochemical reactors, aerospace systems, electrochemical processes, and economic modeling. The book provides theoretical foundations and practical approaches to intelligent control and nonlinear system analysis.
| N° Bulletin | Date / Année de parution | Titre N° Spécial | Sommaire |
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| N° d'Exemplaire / inventaire | Cote | Localisation | Type de Support | Type de Prêt | Statut | Date de Restitution Prévue | Réservation |
|---|---|---|---|---|---|---|---|
| 183601A02 | 530 CAS 1 C1 | BIB-Centrale / Ouvrages | Papier | interne | disponible |