This paper presents a learning Dempster-Shafer model for the detection of buildings in aerial image and range data. The process of evidence assignment in the Dempster-Shafer method is implemented through membership functions in an adaptivenetwork-based fuzzy inference system, where a back propagation learning rule is employed to tune the evidence assignment functions using training samples. The...

The solution of the prediction problem is presented for the finite possibilistic modelling [3,4,6,7]. A recurrent variant of finite possibilistic models is considered. In this variant, we define the regularization condition for constructing a quasi-optimal estimator of fuzzy transition operator (FTO). We construct the discrete recurrent extremal fuzzy process with possibilistic uncertainty, the...

We discuss the use of the fuzzy measure for representing information about uncertain variables. We describe the relationship between the fuzzy measure and the Dempster-Shafer belief structure. A method for generating the fuzzy measures associated with a D-S belief structure is described. We discuss the use of the Shapley index as a means for providing an entropy for fuzzy measures. We introduce...

In this paper, we would like to investigate the relationship between evidential structures (ES)—the basic qualitative structures of Dempster-Shafer theory, and the data table based knowledge representation systems(KRS) subject to rough set analysis. It is shown that an ES has a natural representation as a data table and from a given data table and two of its attributes, an ES can be extracted. ...

This paper addresses a soft computing approach of fusion of signals from different independent sources. The signals may be from different types of primary classifiers. The Dempster Shafer Evidence Accumulation (DSEA) theory provides a robust platform for evidence fusion and it incorporates uncertainty, imprecision and conflicting situations in the process of decision making into a mathematical ...

In this paper, we would like to investigate the relationship between evidential structures (ES)|the basic qualitative structures of Dempster-Shafer theory, and the data table based knowledge representation systems(KRS) subject to rough set analysis. It is shown that an ES has a natural representation as a data table and from a given data table and two of its attributes, an ES can be extracted. ...

Landslide databases and input parameters used for modeling landslide hazard often contain imprecisions and uncertainties inherent in the decision-making process. Dealing with imprecision and uncertainty requires techniques that go beyond classical logic. In this paper, methods of fuzzy k -means classification were used to assign digital terrain attributes to continuous landform classes whereas ...

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 ...

and key words This paper presents an historical overview of the evolution of the notion of probability . The different kinds of probability and the opposition between objectivists (or frequencists) and subjectivists are presented . Then we show how some works, following the wor k by Cox, aim at deducing what is called by others axioms of probabilities, from a given set of basic postulates which...