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Table of contents

  1. Front Matter
  2. A. J. M. M. Weijters, G. A. J. Hoppenbrouwers
    Pages 11-36
  3. J. Henseler
    Pages 37-66
  4. H. J. M. Peters
    Pages 67-81
  5. O. J. Vrieze
    Pages 83-100
  6. E. O. Postma, P. T. W. Hudson
    Pages 101-117
  7. F. C. R. Spieksma
    Pages 119-129
  8. J. H. J. Lenting
    Pages 131-144
  9. E. O. Postma
    Pages 145-156
  10. Y. Crama, A. W. J. Kolen, E. J. Pesch
    Pages 157-174
  11. P. Boekhoudt
    Pages 175-204
  12. W. T. C. van Luenen
    Pages 205-233
  13. P. J. Braspenning
    Pages 247-271
  14. P. T. W. Hudson, E. O. Postma
    Pages 273-287
  15. Back Matter

About this book

Introduction

This book presents carefully revised versions of tutorial lectures given during a School on Artificial Neural Networks for the industrial world held at the University of Limburg in Maastricht, Belgium.
The major ANN architectures are discussed to show their powerful possibilities for empirical data analysis, particularly in situations where other methods seem to fail. Theoretical insight is offered by examining the underlying mathematical principles in a detailed, yet clear and illuminating way. Practical experience is provided by discussing several real-world applications in such areas as control, optimization, pattern recognition, software engineering, robotics, operations research, and CAM.

Keywords

Artificial Neural Networks Kohonen-Netze Kombinatorische Optimierung combinatorial optimization kohonen-networks operations research optimization optimization networks pattern recognition robot robotics software engineering

Bibliographic information

  • DOI https://doi.org/10.1007/BFb0027019
  • Copyright Information Springer-Verlag Berlin Heidelberg 1995
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-59488-8
  • Online ISBN 978-3-540-49283-2
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site