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

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.

2021 ◽  
Vol 27 (1) ◽  
pp. 53-59
Author(s):  
Mladen V. Vassilev-Missana

The inequality \mu^{\frac{1}{\nu}} + \nu^{\frac{1}{\mu}} \leq 1 is introduced and proved, where \mu and \nu are real numbers, for which \mu, \nu \in [0, 1] and \mu + \nu \leq 1. The same inequality is valid for \mu = \mu_A(x), \nu = \nu_A(x), where \mu_A and \nu_A are the membership and the non-membership functions of an arbitrary intuitionistic fuzzy set A over a fixed universe E and x \in E. Also, a generalization of the above inequality for arbitrary n \geq 2 is proposed and proved.


2011 ◽  
Vol 15 ◽  
pp. 2037-2041 ◽  
Author(s):  
Zhang Zhenhua ◽  
Yang Jingyu ◽  
Ye Youpei ◽  
Zhang Qian Sheng

Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1121
Author(s):  
Krassimir Atanassov ◽  
Evgeniy Marinov

In the paper, for the first time, four distances for Circular Intuitionistic Fuzzy Sets (C-IFSs) are defined. These sets are extensions of the standard IFS that are extensions of Zadeh’s fuzzy sets. As it is shown, the distances for the C-IFS are different than those for the standard IFSs. At the moment, they do not have analogues in fuzzy sets theory. Examples, comparing the proposed distances, are given and some ideas for further research are formulated.


2021 ◽  
Vol 27 (4) ◽  
pp. 78-81
Author(s):  
Mladen Vassilev-Missana

In the paper, the inequality \frac{\mu^{\frac{1}{\nu}}}{\nu} + \frac{\nu^{\frac{1}{\mu}}}{\mu} \leq \frac{1}{2\mu\nu} - 1 is introduced and proved. The same inequality is valid for \mu = \mu_A(x), \nu = \nu_A(x), where \mu_A and \nu_A are the membership and the non-membership functions of an arbitrary intuitionistic fuzzy set A over a fixed universe E and x \in E.


2016 ◽  
Vol 10 (10) ◽  
pp. 701-709 ◽  
Author(s):  
He Deng ◽  
Xianping Sun ◽  
Maili Liu ◽  
Chaohui Ye ◽  
Xin Zhou

2017 ◽  
Vol 8 (4) ◽  
pp. 1-13 ◽  
Author(s):  
Bhagawati Prasad Joshi

This article describes how intuitionistic fuzzy sets theory, which is the generalisation of fuzzy sets theory, is a more suitable tool for dealing with imprecise information. The information provided by the decision maker is often imprecise in many situations. So, intuitionistic preference relation is a suitable tool for such cases. The estimation of the priority vector of the intuitionistic preference relation is an important part in decision making. In this article, an intuitionistic fuzzy Choquet integral is proposed and combined with the famous error propagation formula, and developed a method for the priority of an intuitionistic preference relation to estimate the ranking of the considered alternatives. Also, an experiment has been conducted to demonstrate and implementation of the proposed approach.


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