نتایج جستجو برای: interval valued intuitionistic fuzzy matrix

تعداد نتایج: 677878  

In this work, we shall present some novel process to measure the similarity between picture fuzzy sets. Firstly, we adopt the concept of intuitionistic fuzzy sets, interval-valued intuitionistic fuzzy sets and picture fuzzy sets. Secondly, we develop some similarity measures between picture fuzzy sets, such as, cosine similarity measure, weighted cosine similarity measure, set-theoretic similar...

2013
Zhi-yong Bai

This paper proposes an improved score function for the effective ranking order of interval-valued intuitionistic fuzzy sets (IVIFSs) and an interval-valued intuitionistic fuzzy TOPSIS method based on the score function to solve multicriteria decision-making problems in which all the preference information provided by decision-makers is expressed as interval-valued intuitionistic fuzzy decision ...

The aim of this paper is investigate the notion of a generalized interval valued intuitionistic fuzzy number (GIVIFN), which extends the interval valuedintuitionistic fuzzy number. Firstly, the concept of GIVIFNBs is introduced.Arithmetic operations and cut sets over GIVIFNBBs are investigated. Then the values and ambiguities of the membership degree and the non-membership degree and the value ...

2013
Muhammad Shabir Muhammad Rafiq

After the introduction of fuzzy set by Zadeh in 1965 [1], there have been a number of generalizations of this fundamental concept. In 1967, Goguen [2] proposed the concept of L-fuzzy set. The idea of interval valued fuzzy set is given by Zadeh in 1975 [3]. Type 2 fuzzy sets were poposed by Zadeh in [4]. Attanasove introduced intuitionistic fuzzy sets in 1986 [5]. Interval valued intuitionistic ...

Journal: :J. Applied Mathematics 2013
Xiaowen Qi Changyong Liang Jun-ling Zhang

We investigate multiple attribute group decision making (MAGDM) problems with arguments taking the form of interval-valued intuitionistic fuzzy numbers. In order to relieve influence of unfair arguments, a Gaussian distribution-based argument-dependent weighting method and a hybrid support-function-based argument-dependent weighting method are devised by, respectively, measuring support degrees...

2016
Peiyu Ren Yancang Li Huiping Song Fang Zhou

This paper establishes the network marketing performance evaluation index system followed the principles of "scientific, objective, systematic, feasibility and stability". Then use interval-valued intuitionistic fuzzy sets OWA (Ordered Weighted Averaging) operator to calculate the evaluation value. The reason of this paper use interval-valued intuitionistic fuzzy sets is some index value is not...

2014
Yingdong He Huayou Chen Ligang Zhou Jinpei Liu Zhifu Tao

We generalize the power averaging operators to interval-valued Atanassov’s intuitionistic fuzzy environments, and develop a series of generalized interval-valued Atanassov’s intuitionistic fuzzy power aggregation operators. The main advantages of these operators are that they not only accommodate situations in which the input arguments are interval-valued intuitionistic fuzzy numbers (IVIFNs), ...

Journal: :J. Applied Mathematics 2012
Jun-ling Zhang Xiaowen Qi

Two induced aggregation operators with novelly designed TOPSIS order-inducing variables are proposed: Induced Interval-valued Intuitionistic Fuzzy Hybrid Averaging I-IIFHA operator and Induced Interval-valued Intuitionistic Fuzzy Hybrid Geometric I-IIFHG operator. The merit of two aggregation operators is that they can consider additional preference information of decision maker’s attitudinal c...

Jiuying Dong, Shu-Ping Wan

The intuitionistic linguistic set (ILS) is an extension of linguisitc variable. To overcome the drawback of using single real number to represent membership degree and non-membership degree for ILS, the concept of interval-valued intuitionistic linguistic set (IVILS) is introduced through representing the membership degree and non-membership degree with intervals for ILS in this paper. The oper...

Journal: :International Journal of Computational Intelligence Systems 2016

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