In order to process the fuzzy and imprecise information in the evidential reasoning, the scholars have made many attempts to generalize belief and plausibility functions based on the Dempster-Shafer(D-S) evidence theory to fuzzy sets for many decades. A new method for defining the fuzzy closeness degree is put forward in this paper. Based on the closeness degree, another generalization of belie...

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...

In this paper, we implement an anomaly detection system using the Dempster-Shafer method. Using two standard benchmark problems we show that by combining multiple signals it is possible to achieve better results than by using a single signal. We further show that by applying this approach to a real-world email dataset the algorithm works for email worm detection. Dempster-Shafer can be a promis...

This paper reports a study to interpret the surface temperature based on time series and fuzzy measures. We demonstrated method identify uncertainty around data concerning summer monsoon in India. The random variables were standardized, Dempster-Shafer Theory was used generate common goals. Two criteria, represented as numbers, for this purpose. constructed three polynomials illustrate function...

Automated ontology population using information extraction algorithms can produce inconsistent knowledge bases. Confidence values assigned by the extraction algorithms may serve as evidence helping to repair produced inconsistencies. The Dempster-Shafer theory of evidence is a formalism, which allows appropriate interpretation of extractors’ confidence values. The paper presents an algorithm fo...

We present a Dempster-Shafer (DS) approach to finding confidence bounds on the mass of the Higgs boson. Dempster-Shafer is a statistical framework that generalizes Bayesian statistics. DS calculus augments traditional probability by allowing mass to be distributed over power sets of the event space. This eliminates the Bayesian dependence on prior distributions while allowing the incorporation ...

The Dempster-Shafer theory of belief functions is an important approach to deal with uncertainty in AI. In the theory, belief functions are defined on Boolean algebras of events. In many applications of belief functions in real world problems, however, the objects that we manipulate is no more a Boolean algebra but a distributive lattice. In this paper, we extend the Dempster-Shafer theory to t...

Based on World Health Organization (WHO) report in the 2011 Skin diseases still remain common in many rural communities in developing countries, with serious economic and social consequences as well as health implications. Directly or indirectly, skin diseases are responsible for much disability (and loss of economic potential), disfigurement, and distress due to symptoms such as itching or pai...

The financial statement audit is the process of collecting, evaluating, and aggregating relevant items of evidence pertaining to various management assertions related to the financial statement accounts to determine whether the company’s financial statements present fairly its financial position. The Dempster-Shafer theory [1] of belief functions has been argued to be an appropriate framework f...