直觉模糊框架内的证据动态可靠性评估及应用

基于证据理论与直觉模糊集之间的关系,提出了一种新的证据可靠性评估方法,该方法可以在先验知识缺乏的情况下,对各证据源的可靠性进行评估。首先,将证据理论中的基本概率赋值函数(Basic Probability Assignment,BPA)转化为直觉模糊集；然后,通过直觉模糊集之间的相似度度量对各BPA之间的相似度进行计算；在此基础上,提出证据支持度的概念,通过分析证据支持度与证据可靠性之间的关系,获得证据的相对可靠性和绝对可靠性；最后,基于证据折扣运算对原始证据进行修正,采用Dempster组合规则对修正后的证据进行组合。此外,基于直觉模糊框架内的证据可靠性评估,提出了一种多传感器融合方法,通过数值实验对该方法的性能进行了对比分析,结果表明,该方法可以实现对不可靠证据的有效评估。

Dynamic Reliability Evaluation Method of Evidence Based on Intuitionistic Fuzzy Sets and Its Applications

This paper presented a new evidence reliability evaluation method based on evidence theory and intuitionistic fuzzy sets,which can conduct reliability evaluation for different evidence sources when the prior knowledge is lacked.Firstly,the basic probability assignment (BPA) is transformed to intuitionistic fuzzy sets.Then,the similarity among BPAs is calculated through the similarity measure of intuitionistic fuzzy sets.On this basis,the concept of evidence support degree is proposed,and the relative reliability and absolute reliability of evidence can be obtained by analyzing the relationship between supporting degree and reliability of evidence.Lastly,the original evidence is corrected based on evidence discounting operation,and the corrected evidences are combined by Dempster rule.Besides,this paper proposed a multi-sensor fusion method based on the evidence reliability evaluation considering intuitionistic fuzzy sets.Numerical experiment was conducted to analyze its performance.The results show that this method can effectively evaluate the unreliable evidences.