Title of article :
Clustering decomposed belief functions using generalized weights of conflict Original Research Article
Author/Authors :
Johan Schubert، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2008
Pages :
15
From page :
466
To page :
480
Abstract :
We develop a method for clustering all types of belief functions, in particular non-consonant belief functions. Such clustering is done when the belief functions concern multiple events, and all belief functions are mixed up. Clustering is performed by decomposing all belief functions into simple support and inverse simple support functions that are clustered based on their pairwise generalized weights of conflict, constrained by weights of attraction assigned to keep track of all decompositions. The generalized conflict image and generalized weight of conflict image are derived in the combination of simple support and inverse simple support functions.
Keywords :
Clustering , Simulated annealing , Pseudo belief function , Inverse simple support functions , Dempster–Shafer Theory , Decomposition , Generalized weight of conflict , Belief function , Non-consonant belief function
Journal title :
International Journal of Approximate Reasoning
Serial Year :
2008
Journal title :
International Journal of Approximate Reasoning
Record number :
1182501
Link To Document :
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