Credibility reasoning has attracted a lot of attention due to its distinguished power and efficiency in representing uncertainty vagueness within the process decision making. Aiming at problem inaccurate credibility estimation making experts express hesitant preferences better evaluation process, this paper introduces fuzzy linguistic term set into reasoning. First, we propose linguistic-valued...

We have previously (Bx, 2014; MPC, 2015) shown that several state-based bx formalisms can be captured using monadic functional pro-gramming, using the state monad together with possibly other monadiceffects, giving rise to structures we have called monadic bx (mbx). Inthis paper, we develop a coalgebraic theory of state-based bx, and relatethe resulting coalgebraic structure...

Based on credibilistic value-at-risk (CVaR) of regularfuzzy variable, we introduce a new CVaR reduction method fortype-2 fuzzy variables. The reduced fuzzy variables arecharacterized by parametric possibility distributions. We establishsome useful analytical expressions for mean values and secondorder moments of common reduced fuzzy variables. The convex properties of second order moments with ...

This paper describes an X-window based softwareenvironment called HeNCE (Heterogeneous NetworkComputing Environment) designed to assist scientistsin developing parallel programs that run on a networkof computers. HeNCE is built on top of a softwarepackage called P M which supports process manage-ment and communication between a network of hetero-geneous computers. He...

A random fuzzy variable is a function from a credibility space to the set of random variables. Chance distribution is a type of mathematical description of random fuzzy variables. This paper presents a sufficient and necessary condition for chance distribution of random fuzzy variables.

Experimental results are presented of experiments on using Machine Learning algorithms to extract a model of a human control skill The con trol task to be modeled is that of a pilot ying a F ight simulation on a levelled left turn Machine Learning algorithms used include C as a decision tree representative and FOIL and Indlog as Inductive Logic Pro gramming representatives Improvements on the m...

An inverse spanning tree problem is to make the least modification on the edge weights such that a predetermined spanning tree is a minimum spanning tree. In this paper, based on the notion of fuzzy α-minimum spanning tree, the inverse spanning tree problem with fuzzy edge weights is discussed and formulated as a fuzzy programming model with some chance constraints. It shows that when all the e...

coalitional game deals with situations that involve cooperations among players, and there are different solution concepts such as the core,the shapley value and the kernel. in many situations, there is no way to predict the payoff functions except for the expert experiencesand subjective intuitions, which leads to the coalitional game with fuzzy payoffs. within the framework of credibility theo...

Mixed logical linear programming MLLP is an extension of mixed integer linear pro gramming MILP It can represents the discrete elements of a problem with logical propo sitions and provides a more natural modeling framework than MILP It can also have computational advantages partly because it eliminates integer variables when they serve no purpose provides alternatives to the traditional continu...