We give a new interpretation of basic belief assignment transformation into probability distribution, and use directed acyclic network called belief evolution network to describe the causality between the focal elements of a BBA. On this basis, a new probability transformations method called full causality probability transformation is proposed, and this method is superior to all previous method after verification from the process and the result. In addition, using this method combined with disjunctive combination rule, we propose a new probabilistic combination rule called disjunctive transformation combination rule. It has an excellent ability to merge conflicts and an interesting pseudo-Matthew effect, which offer a new idea to information fusion besides the combination rule of Dempster.
翻译：我们对基本信仰分配转换为概率分布进行新的解释,并使用称为信仰进化网络的定向循环网络来描述BBA核心要素之间的因果关系。在此基础上,提出了一种称为完全因果关系概率转换的新概率转换方法,这种方法优于从过程和结果中核查后以前采用的所有方法。此外,我们使用这种方法加上脱影组合规则,提出了一种新的概率组合规则,称为分影转换组合规则。它极有可能合并冲突并产生有趣的假马休效应,除了Dempster的组合规则之外,这为信息融合提供了新的想法。
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