On the fusion of imprecise uncertainty measures using belief structures

Authors:
Ronald R. Yager
Affiliations:
Machine Intelligence Institute, Iona College, New Rochelle, NY 10801, United States and King Saud University, Riyadh, Saudi Arabia1Visiting Distinguished Scientist.1
Venue:
Information Sciences: an International Journal
Year:
2011

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Abstract

Our interest is in the fusion of information from multiple sources when the information provided by the individual sources is expressed in terms of an imprecise uncertainty measure. We observe that the Dempster-Shafer belief structure provides a framework for the representation of a wide class of imprecise uncertainty measures. We then discuss the fusion of multiple Dempster-Shafer belief structures using the Dempster rule and note the problems that can arise when using this fusion method because of the required normalization in the face of conflicting focal elements. We then suggest some alternative approaches fusing multiple belief structures that avoid the need for normalization.