Title :
Automated knowledge acquisition for a fuzzy classification problem
Author :
Whitfort, Tim ; Matthews, Chris ; Jagielska, Ilona
Author_Institution :
Dept. of Inf. Technol., La Trobe Univ., Bundoora, Vic., Australia
Abstract :
Genetic algorithms and neural networks are useful as automated knowledge acquisition tools for Fuzzy Systems. This paper describes the application of these techniques to a well known classification problem, namely the iris species classification problem. The performance of the resulting fuzzy systems exceed that reported for those derived using alternative methods. Preliminary work indicates that the use of genetic algorithms is the more flexible as it allows the simultaneous acquisition of fuzzy set parameters and fuzzy rules
Keywords :
fuzzy neural nets; genetic algorithms; knowledge acquisition; learning by example; pattern classification; Fuzzy Systems; automated knowledge acquisition; expert systems; fuzzy classification problem; fuzzy rule base; fuzzy rules; fuzzy set parameters; genetic algorithms; iris species classification problem; neural networks; Data mining; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Genetic algorithms; Hybrid intelligent systems; Information technology; Iris; Knowledge acquisition; Neural networks;
Conference_Titel :
Artificial Neural Networks and Expert Systems, 1995. Proceedings., Second New Zealand International Two-Stream Conference on
Conference_Location :
Dunedin
Print_ISBN :
0-8186-7174-2
DOI :
10.1109/ANNES.1995.499477
