In pattern analysis, information regarding an object can often be drawn from its surround­ ings. This paper presents a method for handling uncertainty when using context of symbols and texts for analyzing technical drawings. The method is based on Dempster-Shafer theory and possibility theory. 1 Introduction In several pattern analysis problems it is interesting to look at the context in which ...

There is a problem of applying of combining rules to evidence which were got from different information sources in framework of Dempster-Shafer theory. In this work the conflict measure and index of decreasing of ignorance in frame of Dempster-Shafer theory are introduced for characterization of quality of applied combining rules. Those functionals are analyzed on the bodies of evidences of spe...

In this paper, a new Fuzzy Morphology (FM) based on the GeneralizedDempster-Shafer Theory (GDST) is proposed. At first, in order to clarify the similarity ofdefinitions between Mathematical Morphology (MM) and Dempster-Shafer Theory (DST),dilation and erosion morphological operations are studied from a different viewpoint. Then,based on this similarity, a FM based on the GDST is proposed. Unlik...

The research described in this paper addresses issues of designing a computationally effective decision support system which can assist a decision maker in making an optimal choice between several discrete alternatives. A new hybrid approach to multi-attribute decision making under uncertainty incorporating Neural Networks and the Dempster-Shafer theory of evidence is introduced. A neural netwo...

Dempster-Shafer Evidence Theory(DST) enables multi-sensor data fusion, which makes it possible to infer the context. In this paper, we propose about how to use multi-sensor data fusion to infer context in the dynamic circumstances. Dynamic circumstance means a changing of the situation or the surrounding itself, and particularly signifies that there is a changeable factor in a specific environm...

This paper proposes a scheme for activity recognition in sensor based smart homes using Dempster-Shafer theory of evidence. In this work, opinion owners and their belief masses are constructed from sensors and employed in a single-layered inference architecture. The belief masses are calculated using beta probability distribution function. The frames of opinion owners are derived automatically ...

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 ...

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...

As is well known, Dempster-Shafer theory offers an alternative approach to deal with uncertainty reasoning in expert systems and other fields. In this paper, we present two results that relate to the use of the theory. First, we present and analyze four methods to induce uncerioin rules fvlm a training instance set for Dempster-Shafer theory. This is the first attempt to do so, to the best of o...