Artificial Neural Nets and Genetic Algorithms

Proceedings of the International Conference in Innsbruck, Austria, 1993

Editors: Albrecht, Rudolf F., Reeves, Colin, Steele, Nigel C. (Eds.)

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About this book

Artificial neural networks and genetic algorithms both are areas of research which have their origins in mathematical models constructed in order to gain understanding of important natural processes. By focussing on the process models rather than the processes themselves, significant new computational techniques have evolved which have found application in a large number of diverse fields. This diversity is reflected in the topics which are the subjects of contributions to this volume. There are contributions reporting theoretical developments in the design of neural networks, and in the management of their learning. In a number of contributions, applications to speech recognition tasks, control of industrial processes as well as to credit scoring, and so on, are reflected. Regarding genetic algorithms, several methodological papers consider how genetic algorithms can be improved using an experimental approach, as well as by hybridizing with other useful techniques such as tabu search. The closely related area of classifier systems also receives a significant amount of coverage, aiming at better ways for their implementation. Further, while there are many contributions which explore ways in which genetic algorithms can be applied to real problems, nearly all involve some understanding of the context in order to apply the genetic algorithm paradigm more successfully. That this can indeed be done is evidenced by the range of applications covered in this volume.

Table of contents (49 chapters)

  • Workshop Summary

    Steele, Nigel (et al.)

    Pages 1-2

  • The class of refractory neural nets

    Clementi, A. (et al.)

    Pages 3-10

  • The Boltzmann ECE Neural Network: A Learning Machine for Estimating Unknown Probability Distributions

    Kosmatopoulos, Elias B. (et al.)

    Pages 11-17

  • The Functional Intricacy of Neural Networks A Mathematical Study

    Starkermann, Dr. sc. techn., DSc., PhD Rudolf

    Pages 18-24

  • Evolving Neural Feedforward Networks

    Braun, Heinrich (et al.)

    Pages 25-32

Buy this book

eBook $84.99
price for USA in USD (gross)
  • ISBN 978-3-7091-7533-0
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $109.00
price for USA in USD
  • ISBN 978-3-211-82459-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Artificial Neural Nets and Genetic Algorithms
Book Subtitle
Proceedings of the International Conference in Innsbruck, Austria, 1993
Editors
  • Rudolf F. Albrecht
  • Colin Reeves
  • Nigel C. Steele
Copyright
1993
Publisher
Springer-Verlag Wien
Copyright Holder
Springer-Verlag/Wien
eBook ISBN
978-3-7091-7533-0
DOI
10.1007/978-3-7091-7533-0
Softcover ISBN
978-3-211-82459-7
Edition Number
1
Number of Pages
XIII, 737
Number of Illustrations and Tables
403 b/w illustrations
Topics