DocumentCode
2276882
Title
Defuzzification based on fuzzy clustering
Author
Genther, Harald ; Runkler, Thomas A. ; Glesner, Manfred
Author_Institution
Graduiertenkolleg Intelligent Syst. for Inf. & Autom. Technol., Darmstadt Univ. of Technol., Germany
fYear
1994
fDate
26-29 Jun 1994
Abstract
We develop a modified fuzzy clustering algorithm for parametric defuzzification in fuzzy rule base systems. Using examples and basic defuzzification properties we compare defuzzification by clustering with the standard defuzzification methods COG (Center of Gravity) and MOM (Mean of Maxima). Concerning fuzzy sets with forbidden zones the new method proves to be superior. We present how heuristic preprocessing and quality measures are used for appropriate parameter selection
Keywords
fuzzy logic; fuzzy set theory; heuristic programming; knowledge based systems; pattern recognition; COG; Center of Gravity; MOM; Mean of Maxima; euristic preprocessing; fuzzy clustering; fuzzy rule base systems; fuzzy set; parameter selection; parametric defuzzification; Appropriate technology; Automatic control; Clustering algorithms; Color; Data analysis; Fuzzy control; Fuzzy sets; Fuzzy systems; Gray-scale; Message-oriented middleware;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the Third IEEE Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1896-X
Type
conf
DOI
10.1109/FUZZY.1994.343943
Filename
343943
Link To Document