Neurocomputing for Design Automation provides innovative design theories and computational models with two broad objectives: automation and optimization.
This singular book:
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.
Table of Contents
Counter Propagation Neural Network in Structural Engineering
Neural Dynamics Model for Structural Optimization - A Theory
Application of the Neural Dynamics Model to the Plastic Design of Structures
Nonlinear Neural Dynamics Model Optimization of Space Structures
Hybrid CPN-Neural Dynamics Model for Discrete Optimization of Steel Structures
Data Parallel Neural Dynamics Model for Design Optimization for Integrated Design of Large Steel Structures
Distributed Neural Dynamics Algorithms for Optimization of Large Steel Structures
"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