We show how quantum computing can speed up computations related to processing probabilistic, interval, and fuzzy uncertainty.

Probabilistic or stochastic programming is a framework for modeling optimization problems that involve uncertainty.In this paper, we focus on multi-objective linear programmingproblems in which the coefficients of constraints and the righthand side vector are fuzzy random variables. There are several methodsin the literature that convert this problem to a stochastic or<b...

Preferences and uncertainty occur in many real-life problems. We are concerned with the coexistence of preference and uncertainty in the same problem. In particular, we consider uncertainty, defined by the theory of possibility [2], that is one non-probabilistic way of dealing with uncertainty, that comes from lack of data or imprecise knowledge. We propose a method to integrate fuzzy preferenc...

A conceptual experimental framework for 0-theory m d the possibility form of fuzzy set theory is presented. The framework is probabilistic and derived from experimental measurements of evidential support. It is used to quantify the probabilistic masses needed in 0-theory and the membership functions used in fuzzy set theory. Instances in which these two different representations of the same exp...

considering the increasing interest in fuzzy theory and possible applications,the concept of fuzzy metric space concept has been introduced by severalauthors from different perspectives. this paper interprets the theory in termsof metrics evaluated on fuzzy numbers and defines a strong hausdorff topology.we study interrelationships between this theory and other fuzzy theories suchas intuitionis...

Ontology is an effective conceptualism commonly used for the World Wide Web. Fuzzy logic can be incorporated to ontology to represent uncertainty information. To tackle this problem, this paper proposes the FOGA (Fuzzy Ontology Generation framework) for automatic generation of fuzzy ontology on uncertainty information. The FOGA framework comprises the following components: Fuzzy Formal Concept ...

Alternative rules for the aggregation of different sources of information are discussed in the ambit of random set theory, which gives a general framework in the field of the uncertainty measures, containing probabilistic measures, set-based models (interval analysis or more generally convex models), fuzzy sets and possibility theory as particular extreme cases. Analogies and extensions of the ...

in this paper a network comprising alternative branching nodes with probabilistic outcomes is considered. in other words, network nodes are probabilistic with exclusive-or receiver and exclusive-or emitter. first, an analytical approach is proposed to simplify the structure of network. then, it is assumed that the duration of activities is positive trapezoidal fuzzy number (tfn). this paper com...