摘要
证据理论作为一种不确定性推理,广泛应用于人工智能、信息融合等方面。针对高冲突证据在组合过程中易产生各种与事实相悖的结论,提出了基于证据价值的冲突证据合成方法。此方法首先定义了证据价值的标尺,借用欧氏距离的概念计算证据自身价值,并规则化作为权重,然后引入未知项,修正证据源,再利用D-S合成公式对证据进行合成。实例分析表明,此方法在处理冲突证据时是有效、可行的。
The evidence theory is widely applied in artificial intelligence and information fusion fields as a kind of indefinite inference, however, the Dempster combination rule is not reasonable when dealing with conflict evidences and its result is also invalid. To solve this problem, we present a combination method of conflict evidences based on each evidence value. Firstly, the standard scale of the evidence value is defined. Secondly, each evidence value is calculated by the Euclidean distance and they are regularized as their evidence weight. Then an uncertain part is introduced to modify the evidences. Finally, the evidences are combined by using the Dempster-Shafer combination method. The analysis of classical examples shows that the proposal is effective and feasible when evidences conflict.
出处
《计算机工程与科学》
CSCD
北大核心
2016年第8期1715-1720,共6页
Computer Engineering & Science
基金
国家自然科学基金(61170120)
关键词
证据理论
冲突证据
证据价值
修正证据源
evidence theory
conflict evidence evidence value
evidence source modification
