A Parallel Approach to Evidence Combination on Qualitative Markov Trees

摘要：

Dempsters rule of evidence combination is computational expensive. This paper presents a parallel approach to evidence combination on a qualitative Markov tree. Binarization algorithm transforms a qualitative Markov tree into a binary tree based on the computational workload in nodes for an exact implementation of evidence combination. A binary tree is then partitioned into clusters with each cluster being assigned to a processor in a parallel environment. The parallel implementation improves the computational efficiency of evidence combination.

关键词： evidence combination binarization partition cluster parallel processing

作者: Xin Hong Weiru Liu Kenny Adamson

作者单位: School of Computing and Information Engineering University of Ulster at Coleraine, BT52 1SA, UK

会议类型: 国际会议

会议名称: Proceedings of The Fourth International Conference on Parallel and Distribyted Computing,Applications and Technologies(第四届并行与分布式计算应用与技术国际会议)

会议地点: 成都

会议语种:英文

页码: 522-526

在线出版日期: 2003-08-27（万方平台首次上网日期，不代表论文的发表时间）