DocumentCode :
459072
Title :
Algorithm for Fuzzy Relation Identification
Author :
Bara, A.
Author_Institution :
Dept. of Control Syst. & Appl. Informatics, Oradea Univ.
Volume :
1
fYear :
2006
fDate :
25-28 May 2006
Firstpage :
96
Lastpage :
101
Abstract :
Fuzzy model identification of a system can be performed either by subjective or objective methods. Subjective methods assume the describing of system operation in statements of type If...Then... and their summarization in a fuzzy relation. The objective methods are performed in an experimental approach. The second class is a common one and assumes fuzzy model identification without an expert. This presumes an estimation algorithm for the fuzzy relation of a system based on an input-output data set. The paper presents an approach for identification of fuzzy relation based on square prediction error minimization and the results achieved through simulation on the Box-Jenkins data set
Keywords :
fuzzy set theory; identification; minimisation; Box-Jenkins data set; estimation algorithm; fuzzy model identification; fuzzy relation identification; objective method; square prediction error minimization; subjective method; Control systems; Equations; Fuzzy control; Fuzzy sets; Fuzzy systems; Humans; Informatics; Mathematical model; Predictive models; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation, Quality and Testing, Robotics, 2006 IEEE International Conference on
Conference_Location :
Cluj-Napoca
Print_ISBN :
1-4244-0360-X
Electronic_ISBN :
1-4244-0361-8
Type :
conf
DOI :
10.1109/AQTR.2006.254505
Filename :
4022827
Link To Document :
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