DocumentCode :
2250680
Title :
One simple procedure to find the best approximate solution for fuzzy max-average inverse relation
Author :
Yan-Kuen Wu ; Guu, Sy-Ming
Author_Institution :
Dept. of Manage. & Inf. Technol., Vanung Univ., Taoyuan, Taiwan
Volume :
6
fYear :
2010
fDate :
11-14 July 2010
Firstpage :
2806
Lastpage :
2810
Abstract :
Fuzzy relational equations have played an important role in fuzzy modeling and applied to many practical problems. Most theories of fuzzy relational equations based on a premise that the solution set is not empty. However, this is often not the case in practical applications. Recently, Chakraborty et al, presented an efficient algorithm to solve the best approximate solution for the fuzzy relational equations, X o A = I, with max-min composition, where I denotes the identity matrix. In this paper, some theoretical results of the fuzzy relational equations with max-average composition are proposed for this particular problem. One simple procedure finds the best approximate solution for the discussed problem. A numerical example is provided to illustrate the procedure.
Keywords :
approximation theory; fuzzy set theory; matrix algebra; approximate solution; fuzzy max average inverse relation; fuzzy modeling; fuzzy relational equations; identity matrix; Lead; Fuzzy relational equations; max-average composition; the best approximate solution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
Type :
conf
DOI :
10.1109/ICMLC.2010.5580792
Filename :
5580792
Link To Document :
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