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One Simple Procedure to Finding the Best Approximate Solution for a Particular Fuzzy Relational Equation with Max-min Composition

Authors: Yak-Kuen Wu; Chia-Cheng Liu; Yung-Yih Lur; Sy-Ming Guu;

One Simple Procedure to Finding the Best Approximate Solution for a Particular Fuzzy Relational Equation with Max-min Composition

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, XoA=I, with max-min composition, where I denotes the identity matrix. In this paper, new theoretical results are proposed for solving this particular problem. Hence, one simple procedure can be presented to find the best approximate solution quickly. A numerical example is provided to illustrate the procedure.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
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