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...

The objective of this chapter is to provide a semantic framework for fuzzy sets in the theory of rough sets. Rough membership functions are viewed as a special type of fuzzy membership functions interpretable using conditional probabilities. The relationships between fuzzy membership functions and rough membership functions, between core and support of fuzzy set theory and lower and upper appro...

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...

–In this paper, we present an application of intuitionistic fuzzy programming to two person matrix games for the solution with mixed strategies. We use linear membership and non membership functions for such computation. We introduce the intuitionistic fuzzy (IF) goal for the choice of a strategy in a pay-off matrix in order to incorporate ambiguity of human judgments and a player wants to opti...

Many approaches have been proposed for mining fuzzy association rules. The membership functions, which critically influence the final mining results, are difficult to define. In general, multiple criteria are considered when defining membership functions. In this paper, a multi-objective genetic-fuzzy mining algorithm is proposed for extracting membership functions and association rules from qu...

We describe a new method for the fitting of differentiable fuzzy model functions to crisp data. The model functions can be either scalar or multidimensional and need not be linear. The data are n-component vectors. An efficient algorithm is achieved by restricting the fuzzy model functions to sets which depend on a fuzzy parameter vector and assuming that the vector has a conical membership fun...

Abstract: A simple Bayesian approach to nonparametric regression is described using fuzzy sets and membership functions. Membership functions are interpreted as likelihood functions for the unknown regression function, so that with the help of a reference prior they can be transformed to prior density functions. The unknown regression function is decomposed into wavelets and a hierarchical Baye...

In this paper, we study a particular type of convex fractional programming problem and its dual under fuzzy environment. We present appropriate duality results for a fuzzy environment using aspiration level approach. This study use linear membership functions to represent fulfillment of the decision maker’s degree of satisfaction.