Artificial Neural Nets and Genetic Algorithms: "Proceedings Of The International Conference In Innsbruck, Austria, 1993"

Albrecht, Rudolf F., Colin R. Reeves and Nigel C. Steele:

ISBN 10: 3211824596 / ISBN 13: 9783211824597

Published by Springer, 1993

About this Item

756 Seiten nice ex library book Sprache: Englisch Gewicht in Gramm: 1818 27,9 x 21,0 x 4,3 cm, Taschenbuch.

Seller Inventory # 344235

Bibliographic Details

• Title: Artificial Neural Nets and Genetic Algorithms: "Proceedings Of The International Conference In Innsbruck, Austria, 1993"
• Publisher: Springer
• Publication Date: 1993
• Language: English
• ISBN 10: 3211824596
• ISBN 13: 9783211824597
• Binding: Soft cover
• Condition: Gut
• Weight: 1818 grams
• Seller catalogs:
  • Alle Bücher

About this title

Synopsis

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.