نتایج جستجو برای: interval type 2 fuzzy decision matrix
تعداد نتایج: 4159191 فیلتر نتایج به سال:
To address the hesitancy, inconsistency and uncertainty of decision makers’ cognitions, linguistic interval hesitant fuzzy sets (LIHFSs) are efficient tools. This paper focuses on studying the application of LIHFSs. To do this, two correlation coefficients of LIHFSs are defined, which needn't consider the length of elements in LIHFSs or the arrangement of their possible interval values. To addr...
Most decision making methods used to evaluate a system or demonstrate the weak and strength points are based on fuzzy sets and evaluate the criteria with words that are modeled with fuzzy sets. The ambiguity and vagueness of the words and different perceptions of a word are not considered in these methods. For this reason, the decision making methods that consider the perceptions of decision ma...
controller design remains an elusive and challenging problem foruncertain nonlinear dynamics. interval type-2 fuzzy logic systems (it2fls) incomparison with type-1 fuzzy logic systems claim to effectively handle systemuncertainties especially in the presence of disturbances and noises, but lack aformal mechanism to guarantee performance. in contrast, adaptive sliding modecontrol (asmc) provides...
In a previous work, we showed that artificial neural networks (ANNs) could learn the criteria for comparing fuzzy numbers of a real decision maker. A multilayer feed-forward ANN and the backpropagation algorithm, and trapezoidal fuzzy numbers were considered. The criteria of three people were learnt with an ANN. The trained ANN is considered as a personal method of the decision-maker to compare...
In this work, we propose an approach for computing the compromised solution of an LR fuzzy linear system by using of a ranking function when the coefficient matrix is a crisp mn matrix. To do this, we use expected interval to find an LR fuzzy vector, X , such that the vector (AX ) has the least distance from (b) in 1 norm and the 1 cut of X satisfies the crisp linear system AX = b ...
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