A parallel approach to evidence combination on qualitative Markov trees
作者： X. Hong , W. Liu , K. Adamson
DOI: 10.1109/PDCAT.2003.1236357
关键词: Tree (data structure) 、 Theoretical computer science 、 Binary tree 、 Computational resource 、 Parallel algorithm 、 Markov process 、 Markov chain 、 Computer science 、 Fair computational tree logic 、 Decision tree model
摘要: Dempster's rule of evidence combination is computational expensive. We present a parallel approach to on qualitative Markov tree. Binarization algorithm transforms tree into binary based the workload in nodes for an exact implementation combination. A then partitioned clusters with each cluster being assigned processor environment. The improves efficiency
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