【摘要】 证据推理是不确定性推理的一种重要方法,而Dempster合成法则是进行证据推理的核心。针对目前Demp-ster证据合成法则的算法实现不能处理合成结果的焦元为多个假设或命题的集合、近似算法的计算不够精确等问题,提出通过位向量表示识别框架子集,并利用线性表、平衡树等数据结构实现证据合成的3种精确、通用算法。理论分析与仿真实验表明,所实现的算法是有效的。更多还原

【Abstract】 Evidential reasoning is an important method of uncertainty reasoning,while Dempster’s combination rule is the core of evidential reasoning.The focal element of synthesis results may be a collection of a number of assumptions or propositions,but the previous algorithms for Dempster’s combination rule of evidence cannot handle this situation,and their approximation algorithms for the calculation are also not precise enough.Therefore,by implementing subsets of the frame of discernment with bit vectors,three precise general algorithms for Dempster’s combination rule were proposed,which use linear list and balanced tree.Theoretical analysis and simulation results show that the algorithms are effective.更多还原