Abstract
The paper considers generation of decision rules with the help of genetic algorithms. The performed experiments are described, and the results are analyzed. The instances are compared in which different object training sets are used for the pair comparison, i.e. for the evaluation of solutions generated by the genetic algorithm. There are compared the selection operator based on dominance features (Pareto set) and that of scalar function based.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Goldberg, D.E. (1989). Genetic Algorithms in Search, Optimization, and Machine Learning. Reading/MA, USA: Addison-Wesley.
Oliver, J. Finding Decision Rules with Genetic Algorithms. (1994). Al Expert, March, 33–39.
Hwang, C-L. and Yoon, K. (1981). Multiple Attribute Decision Making. Methods and Applications. Lecture Notes in Economics and Mathematical Systems, 186.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1999 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Takahashi, A., Borisov, A. (1999). Determination of Decision Rules on the Basis of Genetic Algorithms. In: Reusch, B. (eds) Computational Intelligence. Fuzzy Days 1999. Lecture Notes in Computer Science, vol 1625. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48774-3_5
Download citation
DOI: https://doi.org/10.1007/3-540-48774-3_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66050-7
Online ISBN: 978-3-540-48774-6
eBook Packages: Springer Book Archive