International Journal of Computational Intelligence Systems

Volume 3, Issue 3, September 2010, Pages 334 - 342

Fuzzy Classifier Design using Modified Genetic Algorithm

Authors
P.Ganesh Kumar
Corresponding Author
P.Ganesh Kumar
Available Online 1 September 2010.
DOI
https://doi.org/10.2991/ijcis.2010.3.3.9How to use a DOI?
Keywords
Fuzzy Classifier, If-then-Rules, Membership function, Genetic Algorithm.
Abstract
Development of fuzzy if- then rules and formation of membership functions are the important consideration in designing a fuzzy classifier system. This paper presents a Modified Genetic Algorithm (ModGA) approach to obtain the optimal rule set and the membership function for a fuzzy classifier. In the genetic population, the membership functions are represented using real numbers and the rule set is represented by the binary string. A modified form of cross over and mutation operators are proposed to deal with the mixed string. The proposed genetic operators help to improve the convergence speed and quality of the solution. The performance of the proposed approach is demonstrated through development of fuzzy classifier for Iris, Wine and Tcpdump data. From the simulation study it is found that the proposed Modified Genetic Algorithm produces a fuzzy classifier which has minimum number of rules and whose classification accuracy is better than the results reported in the literature.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
3 - 3
Pages
334 - 342
Publication Date
2010/09
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
https://doi.org/10.2991/ijcis.2010.3.3.9How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - P.Ganesh Kumar
PY  - 2010
DA  - 2010/09
TI  - Fuzzy Classifier Design using Modified Genetic Algorithm
JO  - International Journal of Computational Intelligence Systems
SP  - 334
EP  - 342
VL  - 3
IS  - 3
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2010.3.3.9
DO  - https://doi.org/10.2991/ijcis.2010.3.3.9
ID  - Kumar2010
ER  -