Uncertainty theory is a branch of mathematics that deals with human uncertainty, and uncertain variable is used to model an uncertain quantity. Uncertainty exists not only in real quantities but also in complex quantities. Complex uncertain variable is mainly used to model a complex uncertain quantity. In uncertainty theory, inverse uncertainty distribution provides an easy way to calculate exp...

Exploiting the coherent medium approximation, I investigate a random walk on objects distributed randomly in continuous space when jump rate depends distance between two adjacent objects. In one dimension, it is shown that decays exponentially long limit, non-diffusive to diffusive transition occurs as density of sites increased. three dimensions, exists has super Gaussian decay.

Uncertainty theory is a branchof axiomaticmathematics formodelingbelief degrees. This theory provides a new mathematical tool for indeterminacy phenomena. Uncertain variable is a fundamental concept in uncertainty theory and used to represent quantities with uncertainty. There are some important characteristics about uncertain variables. The expected value of uncertain variable is its average v...

Design optimization is an important engineering design activity. Performing design optimization in the presence of uncertainty has been an active area of research. The approaches used require modeling the random variables using precise probability distributions or representing uncertain quantities as fuzzy sets. This work, however, considers problems in which the random variables are described ...

This paper considers the minimum spanning tree problem with uncertain random weights in an uncertain random network. The concept of uncertain random minimum spanning tree is initiated for minimum spanning tree problem with uncertain random edge weights. A model is presented to formulate a specific minimum spanning tree problem with uncertain random edge weights involving a distance chance distr...

For modeling decentralized decision-making problems with uncertain random parameters, an uncertain random multilevel programming is proposed. For some special case, an equivalent crisp mathematical programming to the established uncertain random programming is presented. A searching method by integrating uncertain random simulations, neural network and genetic algorithm is produced to search th...

Recent decades have seen great progress in the use of stochastic methods to model aspects of water resource problems. However, the design implications of stochastic modeling have been relatively overlooked. In particular, there is little explicit realization that the stochastic modeling of single-valued, yet uncertain phenomena yields qualitatively different information than the stochastic mode...

The aim of this paper is to use Bayesian statistics to update a probability density function (p.d.f.) related to the tension parameter of the vocal folds, which is one of the main parameters responsible for the changing of the fundamental frequency of a voice signal, generated by a mechanical/mathematical model for producing voiced sounds. Three parameters are considered uncertain in the model ...