Development of a fusion algorithm for uncertain and imprecise information

Distributed decision at a central processing site requires combining local decisions and evidence collected from distributed and heterogeneous information sources. A global decision maker at the fusion center is responsible for transforming the collected evidence into a common knowledge framework so that the converted information can be combined in order to deduce a concise and collective inference. There are two major knowledge-processing mechanisms, i.e., fusion techniques which are based on probabilistic and on possibilistic measures. A method that can process information associated both with probabilistic distribution and possibilistic distribution in described.<
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