Advances of Soft Computing in Engineering

This presentation of advanced soft methods discusses their relationship to genetic and evolutionary algorithms, immune systems, the formulation of deterministic neural networks and Bayesian NN. Numerical efficiency is illustrated through complex engineering structures.

The articles in this book present advanced soft methods related to genetic and evolutionary algorithms, immune systems, formulation of deterministic neural networks and Bayesian NN. Many attention is paid to hybrid systems for inverse analysis fusing soft methods and the finite element method. Numerical efficiency of these soft methods is illustrated on the analysis and design of complex engineering structures.

Contenu
Genetic Algorithms for Design.- Evolutionary and Immune Computations in Optimal Design and Inverse Problems.- Applications of GA and GP to Industrial Design Optimization and Inverse Problems.- Advances in Neural Networks in Computational Mechanics and Engineering.- Selected Problems of Artificial Neural Networks Development.- Neural Networks: Some Successful Applications in Computational Mechanics.