Title :
Set Measure Directed Multi-Source Information Fusion
Author :
Yager, Ronald R.
Author_Institution :
Machine Intell. Inst., Iona Coll., New Rochelle, NY, USA
Abstract :
Our concern here is with the multi-source fusion problem. Two important aspects of this problem are the representation of information provided by the sources and the formulation of the instructions on how to fuse the information provided, which we refer to as the fusion imperative. We investigate the use of a monotonic set measure as a means of representing the fusion imperative. We look at the fusion of various different types of information, precise data, uncertain information such as probabilistic and possibilistic. We also consider the case of imprecise uncertain information such as that represented by a Dempster-Shafer belief structure.
Keywords :
belief maintenance; fuzzy set theory; knowledge representation; sensor fusion; uncertainty handling; Dempster-Shafer belief structure; fusion imperative representation; fuzzy measure representation; information representation; monotonic set measure; possibilistic information; probabilistic information; set measure directed multi-source information fusion; uncertain information; Information representation; Pragmatics; Probability distribution; Q measurement; Uncertainty; Aggregation; Dempster-Shafer; fuzzy measure representation; hard-soft fusion; multi-source fusion; uncertainty modeling;
Journal_Title :
Fuzzy Systems, IEEE Transactions on
DOI :
10.1109/TFUZZ.2011.2159725