Emergent Computing Methods in Engineering Design: Applications of Genetic Algorithms and Neural Networks / Edition 1

by D.E. Grierson, P. Hajela

Overview

The papers in this book show the tremendous potential of emerging computing paradigms such as genetic algorithms, evolutionary computing, and neural networks for solving problems of engineering design.

Product Details

ISBN-13:	9783540608738
Publisher:	Springer Berlin Heidelberg
Publication date:	06/26/1996
Series:	NATO ASI Subseries F: , #149
Edition description:	1996
Pages:	356
Product dimensions:	6.10(w) x 9.25(h) x 0.03(d)

Table of Contents

Local Ecological-Like Evolutionary Computing Framework for Global Robustness.- Genetic Algorithms for the Design of Composite Panels.- A Genetic Algorithm for Structural Design Optimization.- Genetic Algorithms in Optimal Design of Civil Engineering Structures.- Genetic Search Based Hybrid Multimodal Optimization.- The Development of Generic Adaptive Search Tools for Engineering Design.- Evolution Strategy, its Parallelization and Application to Discrete Optimization Problems.- Some Results in Optimal Structural Damping Using a Genetic Algorithm.- Neural Networks for Embedded Control Designs Applied to the “Smarter Car”.- Conceptual Design Using Emergent Computing Techniques.- Role of Emergent Computing Techniques in Multidisciplinary Rotor Blade Design.- Salience Analysis of Mapping Samples for Multilayer Feedforward Networks.- Fuzzy Neural Networks for Control Design.- Efficient Neural Network Techniques for Discrete Optimization Problems.- Neural Network Based Extrapolation Strategies in Structural Analysis and Design.- Neural Networks for Learning and Optimization.- Application of the Simulated Annealing Algorithm to Structural Design.- Structured Multiresolution Neural Networks for Effective Processing of Signals.- The Graph Bi-Partitioning Problem: A Comparison of Search Methods.- A Unified Methodology for Model Synthesis and Recognition of 3-D Objects.- Summary of the Roundtable Discussion.