Non-monotonic Fuzzy Measures and Intuitionistic Fuzzy Sets

Author(s):  
Yasuo Narukawa ◽  
Vicenç Torra
Author(s):  
VicenÇ Torra ◽  
Yasuo Narukawa ◽  
Ronald R. Yager

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.


2013 ◽  
Vol 433-435 ◽  
pp. 736-743 ◽  
Author(s):  
Jie Huang ◽  
Bi Cheng Li ◽  
Yong Jun Zhao

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.


2019 ◽  
Vol 10 (3) ◽  
pp. 445-453
Author(s):  
R. Nagalingam ◽  
S. Rajaram

Author(s):  
Renáta Bartková ◽  
Beloslav Riečan ◽  
Anna Tirpáková

The reference considers probability theory in two main domains: fuzzy set theory, and quantum models. Readers will learn about the Kolmogorov probability theory and its implications in these two areas. Other topics covered include intuitionistic fuzzy sets (IF-set) limit theorems, individual ergodic theorem and relevant statistical applications (examples from correlation theory and factor analysis in Atanassov intuitionistic fuzzy sets systems, the individual ergodic theorem and the Poincaré recurrence theorem). This book is a useful resource for mathematics students and researchers seeking information about fuzzy sets in quantum spaces.


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