Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference in Portoroz, Slovenia, 1999

Dobnikar, Andrej (Editor) / Steele, Nigel C. (Editor) / Pearson, David W. (Editor) / Albrecht, Rudolf F. (Editor)

ISBN 10: 3211833641 / ISBN 13: 9783211833643

Published by Springer, 1999

About this Item

1st edition. 352 pages. 10.75x8.25x0.75 inches. In Stock.

Seller Inventory # x-3211833641

Bibliographic Details

• Title: Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference in Portoroz, Slovenia, 1999
• Publisher: Springer
• Publication Date: 1999
• Language: English
• ISBN 10: 3211833641
• ISBN 13: 9783211833643
• Binding: Paperback
• Condition: Brand New

About this title

Synopsis

From the contents: Neural networks – theory and applications: NNs (= neural networks) classifier on continuous data domains– quantum associative memory – a new class of neuron-like discrete filters to image processing – modular NNs for improving generalisation properties – presynaptic inhibition modelling for image processing application – NN recognition system for a curvature primal sketch – NN based nonlinear temporal-spatial noise rejection system – relaxation rate for improving Hopfield network – Oja's NN and influence of the learning gain on its dynamics Genetic algorithms – theory and applications: transposition: a biological-inspired mechanism to use with GAs (= genetic algorithms) – GA for decision tree induction – optimising decision classifications using GAs – scheduling tasks with intertask communication onto multiprocessors by GAs – design of robust networks with GA – effect of degenerate coding on GAs – multiple traffic signal control using a GA – evolving musical harmonisation – niched-penalty approach for constraint handling in GAs – GA with dynamic population size – GA with dynamic niche clustering for multimodal function optimisation Soft computing and uncertainty: self-adaptation of evolutionary constructed decision trees by information spreading – evolutionary programming of near optimal NNs