Fuzzy probabilities have been widely used in the areas of risk assessment and decision making. Here, we propose a system based on fuzzy probabilities for assessing the intensity of pedestrian collisions and levels of injury. The proposed approach uses possibility probability distributions for demonstrating fuzzy probabilities. A composition of possibility probability distributions (fuzzy probab...

A genemlized possibility-distribution-fuzzy-relationalmodel is proposed considering semantic ambiguity for membership attribute values and ambiguity contained in them. And then the extended relational algebra is shown. In order to eliminate the semantic ambiguity, a membership attribute is attached to each attribute. This clarifies the origin of membership attribute values. What a membership at...

Model checking of linear-time properties based on possibility measures was studied in previous work (Y. Li and L. Li, Model checking of linear-time properties based on possibility measure, IEEE Transactions on Fuzzy Systems, 21(5)(2013), 842-854). However, the linear-time properties considered in the previous work was classical and qualitative, possibility information of the systems was not con...

Fuzzy linear programming with trapezoidal fuzzy numbers (TrFNs) is considered and a new method is developed to solve it. In this method, TrFNs are used to capture imprecise or uncertain information for the imprecise objective coefficients and/or the imprecise technological coefficients and/or available resources. The auxiliary multi-objective programming is constructed to solve the correspondin...

The expected value and variance of a fuzzy variable have been well studied in the literature, and they provide important characterizations of the possibility distribution for the fuzzy variable. In this paper, we seek a similar characterization of the joint possibility distribution for a pair of fuzzy variables. In view of the success of introducing the expected value and variance as fuzzy inte...

Abstract—This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homoge...