DocumentCode :
3225108
Title :
A study in experimental evaluation of neural network and genetic algorithm techniques for knowledge acquisition in fuzzy classification systems
Author :
Jagielska, Ilona ; Matthews, Chris ; Whitfort, T.
Author_Institution :
Dept. of Inf. Syst., Monash Univ., Clayton, Vic., Australia
Volume :
4
fYear :
1997
fDate :
9-12 Jun 1997
Firstpage :
2364
Abstract :
This paper addresses the issue of appropriate evaluation criteria for knowledge acquisition techniques for fuzzy classification systems. It describes an empirical study in which two different systems, one based on neural networks, and the other based on genetic algorithms were developed, applied to three classification problems and evaluated. Comparison of the approaches with the C4.5 inductive algorithm was also carried out
Keywords :
fuzzy logic; genetic algorithms; inference mechanisms; knowledge acquisition; neural nets; pattern classification; C4.5 inductive algorithm; fuzzy classification systems; genetic algorithm; knowledge acquisition; neural network; Australia; Expert systems; Fuzzy sets; Fuzzy systems; Genetic algorithms; Information systems; Information technology; Intelligent networks; Knowledge acquisition; Neural networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks,1997., International Conference on
Conference_Location :
Houston, TX
Print_ISBN :
0-7803-4122-8
Type :
conf
DOI :
10.1109/ICNN.1997.614435
Filename :
614435
Link To Document :
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