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

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Andrej Dobnikar, Nigel C. Steele, David W. Pearson, Rudolf F. Albrecht
Springer Science & Business Media, Jul 15, 1999 - Computers - 352 pages
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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
 

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Contents

Advisory and Programme Committees X
9
A Quantum Associative Memory Based on Grovers Algorithm
22
Improving Generalisation Using Modular Neural Networks
35
Using GMDH Neural Net and Neural Net with Switching Units to Find
50
Rates of Learning in Gradient and Genetic Training of Recurrent Neural Networks
95
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