1st Edition

Soft Computing in Engineering

By Jamshid Ghaboussi Copyright 2018
220 Pages
by CRC Press

220 Pages 147 B/W Illustrations
by CRC Press

220 Pages 147 B/W Illustrations
by CRC Press

Soft computing methods such as neural networks and genetic algorithms draw on the problem solving strategies of the natural world which differ fundamentally from the mathematically-based computing methods normally used in engineering. Human brains are highly effective computers with capabilities far beyond those of the most sophisticated electronic computers. The 'soft computing‘ methods they use... Read more

1 Soft computing 2 Neural networks 3 Neural networks in computational mechanics 4 Inverse problems in engineering 5 Autoprogressive algorithm and self-learning simulation 6 Evolutionary models 7 Implicit redundant representation in genetic algorithm 8 Inverse problem of engineering design

Biography

Jamshid Ghaboussi is Emeritus Professor in Civil and Environmental Engineering at University of Illinois at Urbana-Champaign. He received his doctoral degree from University of California at Berkeley. He has over 40 years of teaching and research experience in computational mechanics and soft computing with applications in structural engineering, geo-mechanics and bio-medical engineering. He has published extensively in these areas and is the inventor in five patents, mainly in the application of soft computing and computational mechanics. He is the co-author of books Numerical Methods in Computational Mechanics (CRC Press) and Nonlinear Computational Solid Mechanics (CRC Press). In recent years he has been conducting research on complex systems and has co-authored a book on Understanding Systems: A Grand Challenge for 21st Century Engineering (World Scientific Publishing).