Adaptative combination rule and proportional conflict redistribution
  rule for information fusion
  This 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.
