Topic
Fuzzy associative matrix
About: Fuzzy associative matrix is a research topic. Over the lifetime, 8027 publications have been published within this topic receiving 194790 citations.
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TL;DR: The paper gave the principle and procedure of fuzzy analytical hierarchy process and studied the properties of fuzzy consistent judgement matrix and the rationality to denote the important comparision of elements by fuzzy consistency judgement matrix.
Abstract: Firstly the paper pointed out the defects of AHP. Then,the paper introduced the concept of fuzzy consistent judgement matrix,and studied the properties of fuzzy consistent judgement matrix and the rationality to denote the important comparision of elements by fuzzy consistent judgement matrix,and the relation between the fuzzy consistent judgement matrix denoting the important comparision and the weigtht denoting the level of importance of element. On the basis of the research,the paper gave the principle and procedure of fuzzy analytical hierarchy process.
137 citations
TL;DR: New inconsistency index of reciprocal matrix with fuzzy elements is introduced and newly designed method of logarithmic least squares for eliciting associated weights is applied.
136 citations
TL;DR: In this paper, the authors considered the case when S is a groupoid and gave the definition of a fuzzy subgroupoid and the fuzzy left (right, two-sided) ideal of S and justified these definitions by showing that a (conventional) subset A of the groupoid S is either a conventional sub-groupoid or a left-right-two-sided ideal if and only the characteristic function fA: S → [0, 1] defined via
Abstract: Given a set S , a fuzzy subset of S is, by definition, an arbitrary mapping f : S → [0, 1] where [0, 1] is the unit segment of the real line. If the set S bears some structure, one may distinguish some fuzzy subsets of S in terms of that additional structure. Rosenfeld [12] was arguably the first who considered the case when S is a groupoid. He gave the definition of a fuzzy subgroupoid and the fuzzy left (right, two-sided) ideal of S and justified these definitions by showing that a (conventional) subset A of a groupoid S is a (conventional) subgroupoid or a left (right, two-sided) ideal of S if and only the characteristic function fA: S → [0, 1] defined via
135 citations
TL;DR: A new fuzzy modeling algorithm is proposed, which partitions the input space more effectively than conventional fuzzy modeling algorithms by taking into consideration the correlation among components of sample data.
Abstract: This paper presents an explanation of a fuzzy model considering the correlation among components of input data. Generally, fuzzy models have a capability of dividing an input space into several subspaces compared to a linear model. But hitherto suggested fuzzy modeling algorithms have not taken into consideration the correlation among components of sample data and have addressed them independently, which results in an ineffective partition of the input space. In order to solve this problem, this paper proposes a new fuzzy modeling algorithm, which partitions the input space more effectively than conventional fuzzy modeling algorithms by taking into consideration the correlation among components of sample data. As a way to use the correlation and divide the input space, the method of principal component is used. Finally, the results of the computer simulation are given to demonstrate the validity of this algorithm.
135 citations