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Engineering - Mechanical Engineering | Advances of Soft Computing in Engineering

Advances of Soft Computing in Engineering

Waszczyszyn, Zenon (Ed.)

2010, VIII, 336 p.

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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.

Content Level » Research

Keywords » design - evolution - evolutionary algorithm - genetic algorithms - genetic programming - neural network - neural networks - soft computing

Related subjects » Artificial Intelligence - Civil Engineering - Computational Intelligence and Complexity - Mechanical Engineering - Mechanics

Table of contents 

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.

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