How to measure gain from the use of intelligent inference ? How can the complexity of the recognition/ classification task be estimated? What is the type of evidence which best suits an .inference mechanism? These questions are addressed here in their theoretical and methodological aspects. Their practical implications are demonstrated with 'real' crop mapping task. For this purpose, simple rul...

We consider a model for the risk-based design of a flood protection dike, and use probability distributions to represent aleatory uncertainty and possibility distributions to describe the epistemic uncertainty associated to the poorly known parameters of such probability distributions. A hybrid method is introduced to hierarchically propagate the two types of uncertainty, and the results are co...

In Dempster-Shafer (DS) theory, multiple information from the distinct information sources are combined to obtain a single Basic Probability Assignment (BPA) function. The well-known combination rule of Dempster-Shafer (DS) provides the weaker solution to the management of conflicting information at the normalization stage. Even this rule fails and provide the counter intuitive results while co...

In this pa�, we suggest marry ing Dempster-Shafer (DS) theory w1th Knowledge Representation (KR). Born out of this marr iage is the defmition of "Dempster-Shafer Belief Bases", abstract data types representing uncertain knowledge that use DS theory for representing strength of belief about our knowledge, and the linguistic structures of an arbitrary KR system for representing the knowledge itse...

This paper is one of many attempts to introduce graphical Markov models within Dempster-Shafer theory of evidence. Here we take full advantage of the notion of factorization, which in probability theory (almost) coincides with the notion of conditional independence. In Dempster-Shafer theory this notion can be quite easily introduced with the help of the operator of composition. Nevertheless, t...

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Picture fuzzy set is the most widely used tool to handle uncertainty with account of three membership degrees, namely, positive, negative, and neutral such that their sum bound up 1. It generalization existing intuitionistic sets. This paper studies interval probability problems picture sets belief structure. The function a vital represent uncertain information in more effective manner. On othe...