Framework development of continuous non-linear Diophantine fuzzy sets and its application to renewable energy source selection. [PDF]
Khan A, Khan S, Rahimzai AA, Abdullah S.
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Integrating decision tools for efficient operations management through innovative approaches. [PDF]
Liu W, Lai X.
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Reassessing China's Regional Modernization Based on a Grey-Based Evaluation Framework and Spatial Disparity Analysis. [PDF]
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Evaluation for the selection of agricultural spraying drones using p, q-Quasirung orthopair fuzzy logic and multi-criteria methods. [PDF]
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Critical Quarterly, EarlyView.
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Data compression with fuzzy relational equations
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Fuzzy reasoning and fuzzy relational equations
Fuzzy Sets and Systems, 1986The paper covers an interesting approach to two basic schemes of reasoning with fuzzy premises namely modus ponens and modus tollens, \[ \begin{alignedat}{2} &A && B \\ &\underline{A_ i \to B_ i,\quad i=1,2,\ldots,N} &\quad& \underline{A_ i \to B_ i,\quad i=1,2,\ldots,N} \\ &B && A \end{alignedat} \] where \(A\), \(A_ i\), \(B\), \(B_ i\) denote fuzzy ...
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On fuzzy relational equations and the covering problem
Information Sciences, 2011In this study, the authors consider finite fuzzy relational equations of the form \(X\circ A= B\), where \(A\) and \(B\) are a fuzzy relation and a fuzzy set, respectively, while \(X\) is the fuzzy set to be determined. The symbol \(\circ\) stands for the max-continuous \(u\)-norm composition operator with ``\(u\)'' being a bivariate function \([0,1]^2\
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