DocumentCode
1714359
Title
Data-driven design of fuzzy system with relational input partition
Author
Gaweda, Adam E. ; Zurada, Jacek M.
Author_Institution
Dept. of Electr. & Comput. Eng., Louisville Univ., KY, USA
Volume
2
fYear
2001
Firstpage
610
Abstract
An approach to data-driven linguistic modeling is presented. The methodology is based on a fuzzy system with relational input partition that allows for transparent modeling of linear dependencies between the inputs. An identification algorithm for this type of fuzzy system is proposed. It automatically finds the strongest dependencies from numerical data. An application example illustrates the usefulness of the proposed approach.
Keywords
fuzzy systems; identification; learning (artificial intelligence); trees (mathematics); binary relations; data-driven linguistic modeling; fuzzy relations; fuzzy system; identification; learning algorithm; relational input partition; transparent modeling; tree; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Humans; Input variables; Multidimensional systems; Mutual information; Partitioning algorithms; Temperature; Tree graphs;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 2001. The 10th IEEE International Conference on
Print_ISBN
0-7803-7293-X
Type
conf
DOI
10.1109/FUZZ.2001.1009028
Filename
1009028
Link To Document