The importance and difficulty of the problem of ranking fuzzy numbers is pointed out. Here we consider approaches to the ranking of fuzzy numbers based upon the idea of associating with a fuzzy number a scalar value, its valuation, and using this valuation to compare and order fuzzy numbers. Specifically we focus on expected value type valuations which are based upon the transformation of a fuz...

In this paper we show that some applications of a fuzzy methodology in medical diagnosis were ”inspired” by probabilistic approaches. Although probability theory and fuzzy set theory describe different facets of uncertainty. In this paper we trace the transformation of statistical measures of diagnostic accuracy to fuzzy occurrence, exclusion and confirmation relations, applied in several fuzzy...

----------------------------------------------------------------------ABSTRACT------------------------------------------------------------------In wireless networks, resource management is a very complicated issue because of scarcity in resources. This paper presents a fuzzy based packet dropping scheme for wireless networks in the context of future generation cellular networks. In this scheme,...

The performance of a genetic algorithm is dependent on the genetic operators, in general, and on the type of crossover operator, in particular. The population diversity is usually used as the performance measure for the premature convergence. In this paper, a fuzzy genetic algorithm is proposed for solving binary encoded combinatorial optimization problems. A new crossover operator and probabil...

Anew integral for capacities is introduced and characterized. It differs from the Choquet integral on non-convex capacities. The main feature of the new integral is concavity, whichmight be interpreted as uncertainty aversion. The integral is extended to fuzzy capacities, which assign subjective expected values to random variables (e.g., portfolios) and may assign subjective probability only to...

This study provides a principal component analysis-fuzzy-support vector regression model for stock price prediction. Stocks with similar historical trends are selected using principal component analysis. Fuzzy information granulation is performed to construct a probability density for stock prices. Support vector regression is implemented to generate a regression function for future price predi...

A modified version of the first-order logic of probability presented in (Halpern 1990) – with probability on possible worlds – makes it possible to formulate an alternative characterisation of fuzzy sets. In this approach, fuzzy sets are no longer seen as primitive entities with an intuitive justification, but rather as structured entities emerging in a suitable logical framework. Some fuzzy te...

In this paper, we propose an interactive decision making method for random fuzzy multiobjective linear programming problems (RFMOLP) through a probability maximization model. In the proposed method, it is assumed that the decision maker has fuzzy goals for not only permissible objective levels of a probability maximization model but also the corresponding distribution function values. Using the...

This paper considers computational methods for obtaining Stackelberg solutions to random fuzzy twolevel linear programming problems. Assuming that the decision makers concerns about the probabilities that their own objective function values are smaller than or equal to certain target values, fuzzy goals of the decision makers for the probabilities are introduced. Using the possibility-based pro...