Abstract In Bayesian rule an unknown parameter is thought to be a quantity whose variation can characterized by prior distribution. Then some data are observed from population distribution function indexed the and then updated according data. The named as posterior Based on uncertainty theory, this paper first makes connection between likelihood function, proposes new method obtain with given S...

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...

rough sets theory is a mathematical approach for analysis of a vague description of objects presented by a well-known mathematician, pawlak (1982, 1991). this paper explores the use of rough sets theory in site location investigation of buried concrete water reservoirs. making an appropriate decision in site location can always avoid unnecessary expensive costs which is very important in constr...

this paper assumes the cell formation problem as a distributed decision network. it proposes an approach based on application and extension of information theory concepts, in order to analyze informational complexity in an agent- based system, due to interdependence between agents. based on this approach, new quantitative concepts and definitions are proposed in order to measure the amount of t...