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Artificial Neural Nets and Genetic Algorithms

Proceedings of the International Conference in Portorož, Slovenia, 1999

  • Conference proceedings
  • © 1999

Overview

Authors:
  1. Andrej Dobnikar

    1. Fakulteta za Računalništvo in Informatiko, Univerza v Ljubljani, Ljubljana, Slovenia

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  2. Nigel C. Steele

    1. Division of Mathematics, School of Mathematical and Information Sciences, Coventry University, Coventry, UK

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  3. David W. Pearson

    1. Laboratoire de Génie Informatique et Ingénierie de Production, Ecole pour les Etudes et la Recherche en Informatique et Electronique, Nimes, France

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  4. Rudolf F. Albrecht

    1. Institut für Informatik, Universität Innsbruck, Innsbruck, Austria

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About this book

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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Table of contents (58 papers)

  1. Front Matter

    Pages I-X
    Download chapter PDF

  3. Neural Networks – Theory and Applications

    1. Comparative Testing of Hyper-Planar Classifiers on Continuous Data Domains

      • David McLean, Zuhair Bandar
      Pages 16-21

    2. A Quantum Associative Memory Based on Grover’s Algorithm

      • Dan Ventura, Tony Martinez
      Pages 22-27

    3. Newton Filters: a New Class of Neuron-Like Discrete Filters and an Application to Image Processing

      • Alexis Quesada-Arencibia, Miguel Alemán-Flores, Roberto Moreno-Diaz Jr.
      Pages 28-34

    4. Improving Generalisation Using Modular Neural Networks

      • David McLean, Zuhair Bandar, Jim O’Shea
      Pages 35-39

    5. The Role and Modelling of Presynaptic Inhibition in the Visual Pathway: Applications in Image Processing

      • Roberto Moreno-Díaz Jr., Alexis Quesada-Arencibia
      Pages 40-45

    6. A Curvature Primal Sketch Neural Network Recognition System

      • Michael Fairbank, Andrew Tuson
      Pages 46-51

    7. Using GMDH Neural Net and Neural Net With Switching Units to Find Rare Particles

      • František Hakl, Marcel Jiřina
      Pages 52-58

    8. A Neural Network Based Nonlinear Temporal-Spatial Noise Rejection System

      • Fa-Long Luo, Rolf Unbehauen, Tertulien Ndjountche
      Pages 59-66

    9. Improving the Performance of the Hopfield Network By Using A Relaxation Rate

      • Xinchuan Zeng, Tony R. Martinez
      Pages 67-72

    10. A New Activation Function in the Hopfield Network for Solving Optimization Problems

      • Xinchuan Zeng, Tony R. Martinez
      Pages 73-77

    11. On-line Learning of Object Representations

      • Horst Bischof, Aleš Leonardis
      Pages 78-85

    12. A neural network model for blast furnace wall temperature pattern classification

      • Henrik Saxén, Leif Lassus
      Pages 86-88

    13. Monitoring an Industrial Plastic Injection Moulding Machine Using Neural Networks

      • N. Costa, A. Cunha, B. Ribeiro
      Pages 89-94

    14. Rates of Learning in Gradient and Genetic Training of Recurrent Neural Networks

      • Ricardo Riaza, Pedro J. Zufiria
      Pages 95-99

    15. Influence of the Learning Gain on the Dynamics of Oja’s Neural Network

      • Pedro J. Zufiria
      Pages 100-106

    16. ATR’s Artificial Brain Project: CAM-Brain Machine (CBM) and Robot Kitten (Robokoneko) Issues

      • Michael Korkin, Hugo de Garis, N. Eiji Nawa, William Dee Rieken
      Pages 107-110
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Authors and Affiliations

  • Fakulteta za Računalništvo in Informatiko, Univerza v Ljubljani, Ljubljana, Slovenia

    Andrej Dobnikar

  • Division of Mathematics, School of Mathematical and Information Sciences, Coventry University, Coventry, UK

    Nigel C. Steele

  • Laboratoire de Génie Informatique et Ingénierie de Production, Ecole pour les Etudes et la Recherche en Informatique et Electronique, Nimes, France

    David W. Pearson

  • Institut für Informatik, Universität Innsbruck, Innsbruck, Austria

    Rudolf F. Albrecht

Bibliographic Information

  • Book Title: Artificial Neural Nets and Genetic Algorithms

  • Book Subtitle: Proceedings of the International Conference in Portorož, Slovenia, 1999

  • Authors: Andrej Dobnikar, Nigel C. Steele, David W. Pearson, Rudolf F. Albrecht

  • DOI: https://doi.org/10.1007/978-3-7091-6384-9

  • Publisher: Springer Vienna

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag Wien 1999

  • Softcover ISBN: 978-3-211-83364-3Published: 15 July 1999

  • eBook ISBN: 978-3-7091-6384-9Published: 06 December 2012

  • Edition Number: 1

  • Number of Pages: X, 352

  • Number of Illustrations: 70 b/w illustrations

  • Topics: Artificial Intelligence, Complexity, Health Informatics, Operations Research/Decision Theory

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