证据理论是一种有用的不确定推理的数学工具,在信息融合、模式识别等领域具有广泛的应用。如何根据获得的证据信息构造合适的基本信任分配即证据建模是应用证据理论的前提,但是证据理论并没有提供通用的证据建模方法,现有的证据建模方法都是面向具体应用的。依据信息的抽象层次,将现有的证据建模方法分为基于特征信息和基于决策信息的建模方法,并分别对其进行了总结分析。最后,讨论了证据建模中存在的问题并指出了未来的研究方向。
The evidence theory is a useful mathematical tool for reasoning with uncertainty and has a wide range of applications in information fusion, pattern recognition, etc. How to construct a proper basic belief as- signment (BBA) based on the obtained evidence information, i. e. , evidence modeling, is the premise of apply- ing evidence theory. However, the evidence theory does not provide a universal method of evidence modeling. The existing evidence modeling methods are all application oriented. According to the abstract level of available information, the exiting evidence modeling methods are classified into feature based method and decision-based method and are summarized respectively. Finally, the problems in evidence modeling are disscussed and the fu- ture research directions are predicted.