Evolutionary computation in dynamic and uncertain environments
This book provides a compilation on the state-of-the-art and recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The motivation for this book arises from the fact that some degree of uncertainty in characterizing any realistic engineering syst...
Enregistré dans:
| Autres auteurs: | , , |
|---|---|
| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Édition: | 1st ed. 2007. |
| Collection: | Studies in Computational Intelligence
51 |
| 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: | • Evolutionary computation in dynamic and uncertain environments, Shengxiang Yang, Yew-Soon Ong, Yaochu Jin, (eds.), Berlin, Springer, 2007, 1 vol. (XXIII-605 p.), Studies in computational intelligence, 978-3-540-49772-1 • Evolutionary Computation in Dynamic and Uncertain Environments, Texte imprimé, 9783540833390 • Evolutionary Computation in Dynamic and Uncertain Environments, Texte imprimé, 9783642080654 • Evolutionary computation in dynamic and uncertain environments, Shengxiang Yang, Yew-Soon Ong, Yaochu Jin, (eds.), Berlin, Springer, 2007, 1 vol. (XXIII-605 p.), Studies in computational intelligence, 978-3-540-49772-1 |
Table des matières:
- Optimum Tracking in Dynamic Environments Explicit Memory Schemes for Evolutionary Algorithms in Dynamic Environments Particle Swarm Optimization in Dynamic Environments Evolution Strategies in Dynamic Environments Orthogonal Dynamic Hill Climbing Algorithm: ODHC Genetic Algorithms with Self-Organizing Behaviour in Dynamic Environments Learning and Anticipation in Online Dynamic Optimization Evolutionary Online Data Mining: An Investigation in a Dynamic Environment Adaptive Business Intelligence: Three Case Studies Evolutionary Algorithms for Combinatorial Problems in the Uncertain Environment of the Wireless Sensor Networks Approximation of Fitness Functions Individual-based Management of Meta-models for Evolutionary Optimization with Application to Three-Dimensional Blade Optimization Evolutionary Shape Optimization Using Gaussian Processes A Study of Techniques to Improve the Efficiency of a Multi-Objective Particle Swarm Optimizer An Evolutionary Multi-objective Adaptive Meta-modeling Procedure Using Artificial Neural Networks Surrogate Model-Based Optimization Framework: A Case Study in Aerospace Design Handling Noisy Fitness Functions Hierarchical Evolutionary Algorithms and Noise Compensation via Adaptation Evolving Multi Rover Systems in Dynamic and Noisy Environments A Memetic Algorithm Using a Trust-Region Derivative-Free Optimization with Quadratic Modelling for Optimization of Expensive and Noisy Black-box Functions Genetic Algorithm to Optimize Fitness Function with Sampling Error and its Application to Financial Optimization Problem Search for Robust Solutions Single/Multi-objective Inverse Robust Evolutionary Design Methodology in the Presence of Uncertainty Evolving the Tradeoffs between Pareto-Optimality and Robustness in Multi-Objective Evolutionary Algorithms Evolutionary Robust Design of Analog Filters Using Genetic Programming Robust Salting Route Optimization Using Evolutionary Algorithms An Evolutionary Approach For Robust Layout Synthesis of MEMS A Hybrid Approach Based on Evolutionary Strategies and Interval Arithmetic to Perform Robust Designs An Evolutionary Approach for Assessing the Degree of Robustness of Solutions to Multi-Objective Models Deterministic Robust Optimal Design Based on Standard Crowding Genetic Algorithm