From adaptive to progressive combination of possibility distributions
Possibility theory offers a nice setting for information combination or data fusion. This attractiveness arises from the elastic constraints that govern the basic concepts pertaining to this theory. Consequently, many combination modes are available ranging from the conjunctive to the disjunctive passing through compromise mode. However, this entails two major problems: how to give a proper possibilistic representation for a given piece of information, and how to choose the proper combination mode. For the latter purpose, Dubois and Prade have proposed an adaptive combination whose behavior moves progressively from conjunctive to disjunctive as soon as the conflict between sources increases. In this paper, we review the proposed rule and one introduces a modified rule called progressive rule that gradually takes conflictual data into account and agrees with robustness purpose. (C) 2002 Elsevier B.V. All rights reserved.
possibility theory data fusion adaptive combination progressive rule modelling