Belief and plausibility functions based on Dempster–Shafer theory have been used to measure uncertainty. They are also widely studied and applied in diverse areas. Numerous studies in the literature have presented various generalizations of belief and plausibility functions to fuzzy sets. However, there are still less generalizations of belief and plausibility functions to intuitionistic fuzzy ...

The notion of fuzzy soft sets is a hybrid soft computing model that integrates both gradualness and parameterization methods in harmony to deal with uncertainty. The decomposition of fuzzy soft sets is of great importance in both theory and practical applications with regard to decision making under uncertainty. This study aims to explore decomposition of fuzzy soft sets with finite value space...

The notion of fuzzy soft sets is a hybrid soft computing model that integrates both gradualness and parametrization methods in harmony to deal with uncertainty. The decomposition of fuzzy soft sets is of great importance in both theory and practical applications with regard to decision making under uncertainty. This study aims to explore decomposition of fuzzy soft sets with finite value spaces...

In the present paper we develop a fuzzy model for the Problem Solving (PS) process by representing its main stages as fuzzy subsets of a set of linguistic labels characterizing the solvers’ performance in each of these stages and we use the total possibilistic uncertainty of the corresponding fuzzy system as a measure of the individuals’ PS skills. Classroom experiments are also provided illust...

Within the framework of fuzzy logic for pattern recognition, we propose a neural network based membership function procedure. The estimate is obtained as the output of a multilayer network trained to minimize a fuzziness measure of the concept to be learnt. This method is shown to be able to deal with probabilistic, resolutional and fuzzy uncertainty. Fuzziness estimation is also made possible ...

Abstract In this paper, definitions of knowledge granulation and rough entropy are proposed based on dominance relations in incomplete fuzzy system (fuzzy information system), and important properties are obtained. It can be found that using the definitions can measure uncertainty of an attribute set in the incomplete fuzzy information systems. A matrix algorithm for attributes reduction is acq...

In this paper, Generalized Aggregated Uncertainty measure 2 (GAU2), as a newuncertainty measure, is considered to evaluate uncertainty in a localization problem in which cameras’images are used. The theory that is applied to a hierarchical structure for a decision making to combinecameras’ images is Dezert-Smarandache theory. To evaluate decisions, an analysis of uncertainty isexecuted at every...

In a two-stage supply chain composed of one manufacturer and one retailer, the pricing and retail service decisions are researched in an uncertain environment. The manufacturing cost, retail cost and market demand are all characterized as uncertain variables. In consideration of the different market power of the manufacturer and the retailer, three non-cooperative games are analyzed, and their ...

The importance of linear fractional programming comes from the fact that many real life problems are based on the ratio of physical or economic values (for example cost/time, cost/volume, profit/cost or any other quantities that measure the efficiency of a system) expressed by linear functions. Usually, the coefficients used in mathematical models are subject to errors of measurement or vary wi...