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
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;
Conference_Titel :
Fuzzy Systems, 2001. The 10th IEEE International Conference on
Print_ISBN :
0-7803-7293-X
DOI :
10.1109/FUZZ.2001.1009028
