This paper responds to a number of criticisms of Dempster-Shafer theory made by Judea Pearl. He criticises Dempster-Shafer belief for not obeying the laws of Bayesian belief," however, these laws lead to well-known problems in the face of ignorance, and seem unreasonably restrictive. It is argued that it is not reasonable to expect a measure of belief to obey Pearl's sandwich principle. The sta...

The Dempster-Shafer theory of evidence accumulation is one of the main tools for combining data obtained from multiple sources. In this paper a special case of combination of two bodies of evidence with non-zero conflict coefficient is considered. It is shown that application of the Dempster-Shafer rule of combination in this case leads to an evaluation of masses of the combined bodies that is ...

The local computation technique (Shafer et a!. 1987, Shafer and Shenoy 1988, Shenoy and Shafer 1986) is used for propagating belief functions in so­ called a Markov Tree. In this paper, we describe an efficient implementation of belief function propagation on the basis of the local computation technique. The presented method avoids all the redundant computations in the propagation process, and ...

This paper describes a novel methodology for predicting fault prone modules. The methodology is based on Dempster-Shafer (D-S) belief networks. Our approach consists of three steps: First, building the Dempster-Shafer network by the induction algorithm; Second, selecting the predictors (attributes) by the logistic procedure; Third, feeding the predictors describing the modules of the current pr...

The Hugin and Shenoy–Shafer architectures are two variations on the jointree algorithm, which exhibit different tradeoffs with respect to efficiency and query answering power. The Hugin architecture is more time–efficient on arbitrary jointrees, avoiding some redundant computations performed by the Shenoy–Shafer architecture. This efficiency, however, comes at the price of limiting the number o...

How to extend standard support vector machines to solve multi-class classification problem and yield the outputs in the frame of Dempster-Shafer theory is useful. The multi-class probability support vector machine is proposed, firstly. The Dempster-Shafer theory based multi-class support vector machine is designed by constructing probability support vector machines for binary classification usi...

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...

In response to the enactment of the Sarbanes-Oxley Act 2002 and of the release of the Public Company Accounting Oversight Board (PCAOB) Auditing Standard No. 5, this study develops a risk-based evidential reasoning approach for assessing the effectiveness of internal controls over financial reporting (ICoFR). This approach provides a structured methodology for assessing the effectiveness of ICo...

Over the years, there have been many proposed methods in set-based tracking. One example of set-based methods is the use of Dempster-Shafer (DS) techniques to support belief-function (BF) tracking. In this paper, we overview the issues and concepts that motivated DS methods for simultaneous tracking and classification/identification. DS methods have some attributes, if applied correctly; but th...

This paper presents an original method for evaluating reliability indices for Multi-State Systems (MSSs) in the presence of aleatory and epistemic uncertainties. In many real world MSSs an insufficiency of data makes it difficult to estimate precise values for component state probabilities. The proposed approach applies the Transferable Belief Model (TBM) interpretation of the Dempster-Shafer t...