Combining testimonial reports from independent and partially reliable information sources is an important problem of uncertain reasoning. Within the framework of Dempster-Shafer theory, we propose a general model of partially reliable sources which includes several previously known results as special cases. The paper reproduces these results, gives a number of new insights, and thereby contribu...

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...

An approach to fuse multiple images based on Dempster-Shafer evidential reasoning is proposed in this article. Dempster-Shafer theory provides a complete framework for combining weak evidences from multiple sources. Such situations typically arise in the image fusion problems, where a ‘real scene’ image has to be estimated from incomplete and unreliable observations. By converting images from t...

As a generalization of Dempster-Shafer theory, the theory of D numbers is a new theoretical framework for uncertainty reasoning. Measuring the uncertainty of knowledge or information represented by D numbers is an unsolved issue in that theory. In this paper, inspired by distance based uncertainty measures for Dempster-Shafer theory, a total uncertainty measure for a D number is proposed based ...

Human resources are an important asset for the company to develop and realize company's goals. One of efforts optimize capacity employees is know their personality. Personality form possessed by individual in behaving all characteristics that distinguish one from another. Knowing personality themselves. Because knowing a person's personality, can maximize potential place certain positions suit ...

This paper introduces the idea of using the Dempster-Shafer theory of evidence with qualitative values. Dempster-Shafer theory is a formalism for reasoning under uncertainty which may be viewed as a generalisation of probability theory with special advantages in its treatment of ambiguous data and the ignorance arising from it. Here we are interested in applying the theory when the numbers that...

We propose an extended relational database model which can model both uncertainty and imprecision in data. This model is based on Dempster-Shafer theory which has become popular in AI as an uncertainty reasoning tool. The definitions of Be1 and Pls functions in Dempster-Shafer theory are extended to compute the beliefs of various comparisons (e.g., equality, less than, etc.) between two basic p...

In the line of our investigation on inductive methods for Semantic Web reasoning, we propose an alternative way for approximate ABox reasoning based on the analogical principle of the nearestneighbors. Once neighbors of a test individual are selected, a combination rule descending from the Dempster-Shafer theory can join together the evidence provided by the neighbor individuals. We show how to...

In this paper we will present criteria for critical evaluation of plausible reasoning systems. We have taken the rational reasoning as our point of comparision: an ideal reasoning system should be able to represent all human knowledge and perform all reasoning tasks, which can be rationally performed. The four main criteria are exible ways of representing uncertainty, the ability for both deduc...