Adaptative combination rule and proportional conflict redistribution rule for information fusion

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dc.creatorFlorea, M. C.
dc.creatorDezert, J.
dc.creatorValin, P.
dc.creatorSmarandache, F.
dc.creatorJousselme, Anne-Laure
dc.date2006-04-11
dc.date.accessioned2026-07-07T07:09:21Z
dc.date.available2026-07-07T07:09:21Z
dc.descriptionThis paper presents two new promising rules of combination for the fusion of uncertain and potentially highly conflicting sources of evidences in the framework of the theory of belief functions in order to palliate the well-know limitations of Dempster's rule and to work beyond the limits of applicability of the Dempster-Shafer theory. We present both a new class of adaptive combination rules (ACR) and a new efficient Proportional Conflict Redistribution (PCR) rule allowing to deal with highly conflicting sources for static and dynamic fusion applications.
dc.descriptionPresented at Cogis '06 Conference, Paris, March 2006
dc.identifierhttps://arxiv.org/abs/cs/0604042
dc.identifierhttp://arxiv.org/abs/cs/0604042
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/111031
dc.subjectArtificial Intelligence
dc.subjectI.4.8
dc.titleAdaptative combination rule and proportional conflict redistribution rule for information fusion
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