chloride ion ingress in concrete is the main reason of concrete corrosion. in real world both uncertainty and stochasticity are main attributes of almost all measurements including testing and modeling of chloride content profile in concrete. regarding these facts new models should be able to represent at least some of the uncertainties in the predictions. in this paper after inspiration from c...

the current study addresses an estimation of investor's optimal portfolio under conditions of uncertainty by using a combination of artificial neural network and markowitz models. for this purpose, such assets as stock prices, house prices, coin and bonds price are used with monthly data over the period 1378-1392. three variables including inflation uncertainty, oil uncertainty and free ma...

The mechanics of transport and ow in a random porous medium are addressed in this paper. The hydraulic properties of the porous medium are modeled as spatial random processes. The heterogeneity of the medium is modeled as a superposition of scales of heterogeneity that are statistically uncorrelated. The stochastic process making up a hydraulic property is thus represented as a linear combinati...

A Bayesian belief network models a joint distribution with an directed acyclic graph representing dependencies among variables and network parameters characterizing conditional distributions. The parameters are viewed as random variables to quantify uncertainty about their values. Belief nets are used to compute responses to queries; i.e., conditional probabilities of interest. A query is a fun...

the notion of a $d$-poset was introduced in a connection withquantum mechanical models. in this paper, we introduce theconditional expectation of  random variables on thek^{o}pka's $d$-poset and prove the basic properties ofconditional expectation on this  structure.

Predictive accuracy is the sum of two kinds of uncertainty–natural variability and modeling uncertainty. This paper addresses the quantification of predictive accuracy of complex simulation models from two perspectives. First, it recognizes that there is a difference between variability and modeling uncertainty; the former can not be reduced with more test information, while the latter can. We ...

We outline in this paper a hybrid method to propagate uncertainty in systems described by trees. Given a system described by a tree where nodes are basic operations and leafs are random variables described by their probability density functions (PDFs), one show that by a combination of exact computations with sampled versions of PDFs one can obtain the PDFs of output variables with great effici...