Intuitionistic fuzzy measures of enterprise Eco-efficiency and its influencing factors

2019 ◽  
Vol 37 (1) ◽  
pp. 185-192
Author(s):  
Zhang Jingjing ◽  
Wang Jiaxin ◽  
Liu Ta ◽  
Han Dongping
Keyword(s):  
Influencing Factors ◽  
Fuzzy Measures ◽  
Intuitionistic Fuzzy

On a Relationship Between Fuzzy Measures and AIFS

2016 ◽  
Vol 24 (06) ◽  
pp. 847-858 ◽  
Author(s):  
VicenÇ Torra ◽  
Yasuo Narukawa ◽  
Ronald R. Yager
Keyword(s):  
Fuzzy Sets ◽  
Intuitionistic Fuzzy Sets ◽  
Fuzzy Measures ◽  
Intuitionistic Fuzzy ◽  
Atanassov Intuitionistic Fuzzy Sets ◽  
Interval Valued

The literature discusses several extensions of fuzzy sets. AIFS, IVFS, HFS, type-2 fuzzy sets are some of them. Interval valued fuzzy sets is one of the extensions where the membership is not a single value but an interval. Atanassov Intuitionistic fuzzy sets, for short AIFS, are defined in terms of two values for each element: membership and non-membership. In this paper we discuss AIFS and their relationship with fuzzy measures. The discussion permits us to define counter AIFS (cIFS) and discretionary AIFS (dIFS). They are extensions of fuzzy sets that are based on fuzzy measures.

Target Threat Assessment Based on Intuitionistic Fuzzy Sets Choquet Integral

2013 ◽  
Vol 433-435 ◽  
pp. 736-743 ◽  
Author(s):  
Jie Huang ◽  
Bi Cheng Li ◽  
Yong Jun Zhao
Keyword(s):  
Fuzzy Sets ◽  
Membership Function ◽  
Information Fusion ◽  
Choquet Integral ◽  
Threat Assessment ◽  
Intuitionistic Fuzzy Sets ◽  
Fuzzy Sets Theory ◽  
Fuzzy Measures ◽  
Intuitionistic Fuzzy ◽  
Sets Theory

For the problem that threat assessment often has some uncertainty and the correlation exist among threat factors, a technique based on intuitionistic fuzzy sets Choquet integral is proposed with intuitionistic fuzzy sets and fuzzy integral being introduced into information fusion area. First, threat estimators based on different factors are constructed with intuitionistic fuzzy sets theory. The uncertainty of each estimator is represented with membership function and non-membership function. Then, the significances of the estimators are modeled with fuzzy measures. Subsequently, threat assessment results are obtained using Choquet integral. Finally, the proposed method is validated through the air combat threat assessment of 20 typical targets.

INTUITIONISTIC FUZZY LINGUISTIC QUANTIFIERS BASED ON INTUITIONISTIC FUZZY-VALUED FUZZY MEASURES AND INTEGRALS

2009 ◽  
Vol 17 (03) ◽  
pp. 427-448 ◽  
Author(s):  
LICONG CUI ◽  
YONGMING LI ◽  
XIAOHONG ZHANG
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Integral ◽  
Fuzzy Measures ◽  
Intuitionistic Fuzzy ◽  
Norm Form ◽  
Form Theorem ◽  
Linguistic Quantifier ◽  
Fuzzy Linguistic Quantifiers ◽  
Linguistic Quantifiers ◽  
Fuzzy Linguistic

In this paper, we generalize Ying's model of linguistic quantifiers [M.S. Ying, Linguistic quantifiers modeled by Sugeno integrals, Artificial Intelligence, 170 (2006) 581-606] to intuitionistic linguistic quantifiers. An intuitionistic linguistic quantifier is represented by a family of intuitionistic fuzzy-valued fuzzy measures and the intuitionistic truth value (the degrees of satisfaction and non-satisfaction) of a quantified proposition is calculated by using intuitionistic fuzzy-valued fuzzy integral. Description of a quantifier by intuitionistic fuzzy-valued fuzzy measures allows us to take into account differences in understanding the meaning of the quantifier by different persons. If the intuitionistic fuzzy linguistic quantifiers are taken to be linguistic fuzzy quantifiers, then our model reduces to Ying's model. Some excellent logical properties of intuitionistic linguistic quantifiers are obtained including a prenex norm form theorem. A simple example is presented to illustrate the use of intuitionistic linguistic quantifiers.

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