We discuss the role of fuzzy sets in modeling business rules. The technology involved in fuzzy systems modeling is described. We next introduce some ideas from the Dempster-Shafer theory of evidence. We use the Dempster-Shafer framework to provide a machinery for including randomness in the fuzzy systems

Dempster-Shafer evidence theory is an efficient method to process uncertain, incomplete and vague information in data fusion. The combination of conflicting bodies of evidence has been one of the most important issues in Dempster-Shafer evidence theory since the example of counter-intuitive results produced by Dempster’s rule was found. Based on the framework of the Dempster-Shafer evidence the...

In social media, trust and distrust among users are important factors in helping users make decisions, dissect information, and receive recommendations. However, the sparsity and imbalance of social relations bring great difficulties and challenges in predicting trust and distrust. Meanwhile, there are numerous inducing factors to determine trust and distrust relations. The relationship among i...

We introduce a general theory of epistemic random fuzzy sets for reasoning with or crisp evidence. This framework generalizes both the Dempster-Shafer belief functions, and possibility theory. Independent are combined by generalized product-intersection rule, which extends Dempster's rule combining product conjunctive combination distributions. Gaussian numbers their multi-dimensional extension...

This contribution deals with a belief processing which enables managing of multiple and overlapping elements of a frame of discernment. An outline of the Dempster-Shafer theory for such cases is presented, including several types of constraints for simplification of its large computational complexity. DSmT — a new theory rapidly developing the last five years — is briefly introduced. Finally, i...

How to manage conflict is still an open issue in Dempster-Shafer evidence theory. The correlation coefficient can be used to measure the similarity of evidence in Dempster-Shafer evidence theory. However, existing correlation coefficients of belief functions have some shortcomings. In this paper, a new correlation coefficient is proposed with many desirable properties. One of its applications i...

In this paper, speaker identification using the Dempster-Shafer theory of evidence is discussed. The objective is to use the complementary information present from different classifiers to fuse the classification results into a single decision. Here, we use a decreasing function of the distance (of the classifiers) as our belief function. In the case of speaker identification, we show that a co...

Software Quality and Reliability Prediction Using Dempster-Shafer Theory