The factors influencing dam safety are complex and their impact on dam safety is fuzzy and uncertain. With the introduction of the Dempster-Shafer theory, BP neural network and Jousselme distance function into dam safety monitoring, a new method for dam safety evaluation is explored. Firstly, the basic probability assignment of the factors influencing dam safety is determined by BP neural netwo...

1 Faculty of Electronics and Telecommunications, Multimedia Dept. Bd. V. Parvan 2, 300223 Timisoara, Romania, e-mail: [email protected], [email protected] 2 Mathematics, Image and Applications Laboratory, University of La Rochelle Avenue Michel Crepeau 17042 La Rochelle, France, e-mail: [email protected], [email protected] Abstract – Detection of moving objects has been widel...

It is critical to build an effective prediction model to improve the accuracy of financial distress prediction. Some existing literatures have demonstrated that single classifier has limitations and combination of multiple prediction methods has advantages in financial distress prediction. In this paper, we extend the research of multiple predictions to integrate with rough set and Dempster–Sha...

Stochastic Multicriteria Acceptability Analysis (SMAA) is a family of methods to aid decision makers (DMs) in discrete decision making problems. SMAA methods are capable of handling preference information of various types. The imprecise preferences of multiple DMs can for example be represented by a joint probability distribution for criteria weights. Dempster-Shafer theory with Analytic Hierar...

We develop a new approach for decision making with Dempster-Shafer theory of evidence by using uncertain information represented in the form of interval numbers. We suggest the use of different types of uncertain aggregation operators in the problem. Then, we obtain new aggregation operators such as the belief structure uncertain ordered weighted averaging (BSUOWA) operator and the BS uncertain...

The modeling of epistemic knowledge is a necessity of most systems dealing with some sort of artificial reasoning. There a re several formalisms able to mathematically model someone’s degrees of belief. A very popular one is the Bayesian Theory, which is based on a prior knowledge of a probability distribution. Another model is the Theory of Evidence, or DempskrShafer Theory, which provides a m...

The Dempster-Shafer theory gives a solid basis for reasoning appl icat ions characterized by uncertainty. A key feature of the theory is that proposi t ions are represented as subsets of a set which represents a hypothesis space. Th is power set along w i t h the set operations is a Boolean algebra. Can we generalize the theory to cover a rb i t ra ry Boolean algebras ? We show that the answer ...

The origins of Dempster-Shafer theory (DST) go back to the work by Dempster (1967) who developed a system of upper and lower probabilities. Following this, his student Shafer (1976), in his book “A Mathematical Theory of Evidence” added to Dempster’s work, including a more thorough explanation of belief functions. In summary, it is a methodology for evidential reasoning, manipulating uncertaint...

This paper deals with the use of Bayesian networks to compute system reliability. The reliability analysis problem is described and the usual methods for quantitative reliability analysis are presented within a case study. Some drawbacks that justify the use of Bayesian networks are identified. The basic concepts of the Bayesian networks application to reliability analysis are introduced and a ...