Neurocomputing for Design Automation : Computer Aided Engineering - Hyo Seon Park

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Neurocomputing for Design Automation

By: Hyo Seon Park

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Hardcover | 22 May 1998 | Edition Number 1

At a Glance

Hardcover
240 Pages

Dimensions(cm)
23.4 x 15.6 x 1.91

Hardcover

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Neurocomputing for Design Automation provides innovative design theories and computational models with two broad objectives: automation and optimization.
This singular book:

Presents an introduction to the automation and optimization of engineering design of complex engineering systems using neural network computing

Outlines new computational models and paradigms for automating the complex process of design for unique engineering systems, such as steel highrise building structures

Applies design theories and models to the solution of structural design problems

Integrates three computing paradigms: mathematical optimization, neural network computing, and parallel processing
The applications described are general enough to be applied directly or by extension to other engineering design problems, such as aerospace or mechanical design. Also, the computational models are shown to be stable and robust - particularly suitable for design automation of large systems, such as a 144-story steel super-highrise building structure with more than 20,000 members.
The book provides an exceptional framework for the automation and optimization of engineering design, focusing on a new computing paradigm - neural networks computing. It presents the automation of complex systems at a new and higher level never achieved before.

Industry Reviews

"The authors show how these models can also be applied to aerospace, mechanical and electronic designs because these disciplines share two characteristics: they are open ended..."-Civil Engineering, February 1999

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Introduction	p. 1
Counterpropagation Neural Networks in Structural Engineering	p. 5
Neural Dynamics Model for Structural Optimization - Theory	p. 35
Application of the Neural Dynamics Model to the Plastic Design of Structures	p. 57
Nonlinear Neural Dynamics Model for Optimization of Space Structures	p. 79
Hybrid CPN-Neural Dynamics Model for Discrete Optimization of Steel Structures	p. 109
Data Parallel Neural Dynamics Model for Integrated Design of Large Steel Structures	p. 135
Distributed Neural Dynamics Algorithms for Optimization of Large Steel Structures	p. 175
References	p. 199
Index	p. 217
Table of Contents provided by Blackwell. All Rights Reserved.

Neurocomputing for Design Automation

At a Glance

Hardcover

Industry Reviews

Shipping

How to return your order

Defective items

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