DocumentCode :
2133929
Title :
System modelling and fuzzy relational identification
Author :
De Oliveira, J. Valente ; Lemos, J. Miranda
Author_Institution :
INESC, Lisboa, Portugal
fYear :
1993
fDate :
1993
Firstpage :
1074
Abstract :
Fuzzy relation equations are a suitable framework for modeling physical processes. However, their applications to identification and modeling problems are still weakly explored. To fill this gap, two related critical issues are addressed: the construction of numeric/linguistic interfaces and the computation of the fuzzy relation. An optimizing algorithm is adopted for the construction of the numeric/linguistic interface. Adaptive learning is proposed for determining approximated solutions for systems of fuzzy relation equations, namely for their extended versions. Simulation results are provided showing both fast learning rates and good performance for the derived model
Keywords :
adaptive systems; fuzzy set theory; identification; adaptive learning; approximated solutions; extended versions; fuzzy relation equations; fuzzy relational identification; learning rates; numeric/linguistic interfaces; optimizing algorithm; physical processes; Computational modeling; Control systems; Discrete transforms; Fuzzy control; Fuzzy sets; Fuzzy systems; Nonlinear equations; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 1993., Second IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-0614-7
Type :
conf
DOI :
10.1109/FUZZY.1993.327365
Filename :
327365
Link To Document :
بازگشت