Title :
A clustering assisted method for fuzzy rule extraction and pattern classification
Author :
Kuo, H. ; Gedeon, T.D. ; Wong, P.M.
Author_Institution :
Sch. of Comput. Sci. & Eng., Murdoch Univ., WA, Australia
Abstract :
The fuzzy classification method developed by S. Abe and M.S. Lan (1995) has been improved. This method extracts fuzzy rules directly from numerical data. The paper shows how preprocessing input data using clustering may help the classification accuracy in some cases. The proposed method is compared with Abe and Lan´s fuzzy classification method with a data set obtained from an oil reservoir in the North West Shelf in Australia and the Fisher Iris data
Keywords :
fuzzy set theory; knowledge based systems; oil technology; pattern clustering; petroleum industry; Australia; Fisher Iris data; North West Shelf; classification accuracy; clustering assisted method; data set; fuzzy classification method; fuzzy rule extraction; input data preprocessing; numerical data; oil reservoir; pattern classification; Australia; Data mining; Fuzzy sets; Fuzzy systems; Hydrocarbon reservoirs; Iris; Optimization methods; Pattern classification; Petroleum; Testing;
Conference_Titel :
Neural Information Processing, 1999. Proceedings. ICONIP '99. 6th International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-5871-6
DOI :
10.1109/ICONIP.1999.845677
