1
Assistant Professor, Ferdowsi University of Mashhad.
2
Professor, Tehran University.
3
Assistant Professor, Tehran University.
Abstract
In recent years many methods to generate fuzzy rules based on training samples is proposed. One of the methods that recently suggested is Chen & Tsai’s method that was presented in 2008. This method was based on three indices: Attribute Threshold Value ( ), Classification Threshold Value ( ) and Level Threshold Value ( ). This method has a higher average classification accuracy rate than other methods available. In part of generating interim rules, Authors have provided suggestions to improve method and they used modified method in a case study. What in this research has been considered is the examining of CT08 improved method in an applied field on the one hand, and presentation of a classification system for mobile sets on the other hand. Improved method depicted higher accuracy than original method (about 0.2 in mobile set subject).
Motahhari Farimani, N., Momeni, M. & Yazdani, H. R. (2013). Generating Fuzzy Rules from Training Instances for Fuzzy Classification Systems. Journal of Industrial Management Perspective, 3(3), 163–188.
MLA
Motahhari Farimani, N., Momeni, M., & Yazdani, H. R. "Generating Fuzzy Rules from Training Instances for Fuzzy Classification Systems", Journal of Industrial Management Perspective, 3, 3, 2013, 163–188.
HARVARD
Motahhari Farimani, N., Momeni, M., & Yazdani, H. R. (2013). 'Generating Fuzzy Rules from Training Instances for Fuzzy Classification Systems', Journal of Industrial Management Perspective, 3(3), pp. 163–188.
CHICAGO
Motahhari Farimani, N., Momeni, M. & Yazdani, H. R., "Generating Fuzzy Rules from Training Instances for Fuzzy Classification Systems." Journal of Industrial Management Perspective, 3 3 (2013): 163–188,
VANCOUVER
Motahhari Farimani N., Momeni M., Yazdani H. R. Generating Fuzzy Rules from Training Instances for Fuzzy Classification Systems. J Ind Manag Persp. 2013;3(3):163–188 (In Persian).
