DocumentCode
3263486
Title
Design of fuzzy inference systems using regression trees
Author
Lim, Sook ; Kim, Sung Chun
Author_Institution
Dept. of Comput. Eng., YoSu Nat. Fisheries Univ., ChonNam, South Korea
Volume
1
fYear
1995
fDate
Nov/Dec 1995
Firstpage
345
Abstract
In this paper, we describe a design methodology for fuzzy inference systems based on regression trees. Fuzzy associative memory banks with symmetric triangular fuzzy membership functions are constructed by using sample data statistics of regression tree partitions. We propose a new fuzzy inference method that takes the membership of the average of normalized input features in the antecedent of a production rule
Keywords
associative processing; content-addressable storage; fuzzy neural nets; inference mechanisms; performance evaluation; statistical analysis; trees (mathematics); fuzzy associative memory; fuzzy inference systems; performance evaluation; regression trees; sample data statistics; symmetric triangular fuzzy membership functions; Aquaculture; Associative memory; Decision trees; Design engineering; Design methodology; Fuzzy control; Fuzzy sets; Fuzzy systems; Humans; Production; Regression tree analysis; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.488122
Filename
488122
Link To Document