Adaptative combination rule and proportional conflict redistribution rule for information fusion
Artificial Intelligence
2007-05-23 v1
Abstract
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.
Keywords
Cite
@article{arxiv.cs/0604042,
title = {Adaptative combination rule and proportional conflict redistribution rule for information fusion},
author = {M. C. Florea and J. Dezert and P. Valin and F. Smarandache and Anne-Laure Jousselme},
journal= {arXiv preprint arXiv:cs/0604042},
year = {2007}
}
Comments
Presented at Cogis '06 Conference, Paris, March 2006