نتایج جستجو برای: type 2 fuzzy demand

تعداد نتایج: 3652463  

Journal: :International Journal of Approximate Reasoning 2017

2012
M. Mutingi C. Mbohwa

Real-world manufacturing supply chain systems are characterised by imprecise and dynamic factors. As a result, decision-making takes place in a complex, dynamic and fuzzy environment in which managerial goals and the impacts of possible actions are not precisely known. In a demand driven manufacturing supply chain system, the presence of a fuzzy demand is a serious cause for concern. The presen...

Journal: :IEEE Transactions on Fuzzy Systems 2021

In many contexts, type-2 fuzzy sets (T2 FS) are obtained from a type-1 set to which we wish add uncertainty. However, in the current representation, there is no restriction on shape of footprint uncertainty and embedded (ESs) that can be considered acceptable. This leads, usually, loss semantic relationship between T2 FS concept it models. As consequence, interpretability some ESs explainabilit...

Journal: :IEEE Transactions on Fuzzy Systems 2002

Journal: :Advances in Pure Mathematics 2018

Journal: :International Journal of Engineering and Innovative Technology 2021

Liangliang Dai Na Hu Yanbing Gong

This paper proposes a new approach based on Bonferroni mean operator and possibility degree to solve fuzzy multi-attribute decision making (FMADM) problems in which the attribute value takes the form of interval type-2 fuzzy numbers. We introduce the concepts of interval possibility mean value and present a new method for calculating the possibility degree of two interval trapezoidal type-2 fuz...

Journal: :Applied sciences 2021

The article presents a multidimensional type 2 epistemic fuzzy arithmetic (MT2EF-arithmetic) based on the new body definition of set (T2FS), which in authors’ opinion, is more suitable for computing than current versions (FA) border T2FS. proposed MT2EF-arithmetic designed variables and has mathematical properties that allow obtaining universal algebraic calculation results. performs calculatio...

Journal: :Journal of Computer Science and Cybernetics 2012

In this paper an adaptive neuro fuzzy inference system based on interval Gaussian type-2 fuzzy sets in the antecedent part and Gaussian type-1 fuzzy sets as coefficients of linear combination of input variables in the consequent part is presented. The capability of the proposed method (we named ANFIS2) to function approximation and dynamical system identification is shown. The ANFIS2 structure ...

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