This paper presents the theory and formalism of fuzzy causal probabilistic networks (FCPN) and show their current and potential applications in multisensor data fusion. A fuzzy causal probabilistic network (FCPN) is a directed acyclic graph representing the joint probability distributions of a set of fuzzy random variables describing a problem domain. FCPNs extend causal probabilistic networks ...

In this paper, we deal with multiobjective integer programming problems involving random variable coefficients in objective functions and/or constraints. After reformulation of them on the basis of a probability maximization model for the chance constrained programming, incorporating fuzzy goals of the decision maker for the objective functions, we propose an interactive fuzzy satisficing metho...

Fuzzy random variables have been introduced by Puri and Ralescu as an extension of random sets. In this paper, we ®rst introduce a real-valued generalized measure of the ``relative variation'' (or inequality) associated with a fuzzy random variable. This measure is inspired in Csisz ar's f-divergence, and extends to fuzzy random variables many well-known inequality indices. To guarantee certain...

One-way analysis of covariance is a popular and common statisticalmethod, wherein the equality of the means of several random variables whichhave a linear relationship with a random mathematical variable, is tested. Inthis study, a method is presented to improve the one-way analysis of covari-ance when there is an uncertainty in accepting the statistical hypotheses. Themethod deals with a fuzzy...

This study introduces the fuzzy Lyapunov function to the fuzzy PID control systems, modified fuzzy systems, with an optimized robust tracking performance. We propose a compound search strategy called conditional linear matrix inequality (CLMI) approach which was composed of the proposed improved random optimal algorithm (IROA) concatenated with the simplex method to solve the linear matrix ineq...

The application of fuzzy set theory to renewal reward processes is proposed in this paper. The reward is modeled as a fuzzy random variable. A theorem which presents the long-run average fuzzy reward per unit time is stated. A procedure to obtain the best T-age replacement policy with fuzzy cost structure is developed. The original problem is transformed into a nonlinear program in order to eva...

A weighted linear regression model with impercise response and p-real explanatory variables is analyzed. The LR fuzzy random variable is introduced and a metric is suggested for coping with this kind of variables. A least square solution for estimating the parameters of the model is derived. The result are illustrated by the means of some case studies.