A fuzzy cognitive map is a graphical means of representing arbitrarily complex models of interrelations between concepts. The purpose of this paper is to describe a dynamic fuzzy cognitive map based on the random neural network model. Previously, we have developed a random fuzzy cognitive map and illustrated its application in the modeling of processes. The adaptive fuzzy cognitive map changes ...

Random utility models have been widely used in many diverse fields. Considering utility as a random variable opened many new analytical doors to researchers in explaining behavioral phenomena. Introducing and incorporating the random error term into the utility function had several reasons, including accounting for unobserved variables. This paper incorporates fuzziness into random utility mode...

a memory control for t-s fuzzy discrete-time systems with sto- chastic input delay is proposed in this paper. dierent from the common assumptions on the time delay in the existing literatures, it is assumed in this paper that the delays vary randomly and satisfy some probabilistic dis- tribution. a new state space model of the discrete-time t-s fuzzy system is derived by introducing some stocha...

We introduce and study the general nonlinear random H,η -accretive equations with random fuzzy mappings. By using the resolvent technique for the H,η -accretive operators, we prove the existence theorems and convergence theorems of the generalized random iterative algorithm for this nonlinear random equations with random fuzzy mappings in q-uniformly smooth Banach spaces. Our result in this pap...

In this paper, a model of an optimal control problem with chance constraints is introduced. The parametersof the constraints are fuzzy, random or fuzzy random variables. Todefuzzify the constraints, we consider possibility levels.  Bychance-constrained programming the chance constraints are converted to crisp constraints which are neither fuzzy nor stochastic and then the resulting classical op...

We firstly introduce an evaluation method of fuzzy numbers called the mean value with evaluation measures. Then, using this notion, a stopping game model with fuzzy random variables could be formulated. When a sequence of fuzzy-valued random variables(fuzzy RV) are observed, the important problem is how to treat and analyze the model. Previously the observed fuzzy RV’s are evaluated by probabil...

It is known that from the purely mathematical viewpoint, fuzzy sets can be interpreted as equivalent classes of random sets. This interpretations helps to teach fuzzy techniques to statisticians and also enables us to apply results about random sets to fuzzy techniques. The problem with this interpretation is that it is too complicated: a random set is not an easy notion, and classes of random ...

The paper presents quite general weak and strong laws of large numbers for weighted sums of triangular arrays of random fuzzy sets. The proofs of the results rely on an appropriate identification of random fuzzy sets with random elements in Banach spaces which satisfy a useful convexity property.

A new two-step fuzzy filter that adopts a fuzzy logic approach for the enhancement of images corrupted with impulse noise is presented in this paper. The filtering method (entitled as Fuzzy Random Impulse Noise Reduction method (FRINR)) consists of a fuzzy detection mechanism and a fuzzy filtering method to remove (random-valued) impulse noise from corrupted images. Based on the criteria of pea...