摘要
模糊证据(D-S)理论基于非空集合。其隶属函数用比较/增量/三分法或事先人为确定,再试验验证。根据信息粒度和可能性,把D-S推广到模糊集,将期望确定和可能性定义为信任和似真度推广函数,并引入信任、似然及类概率函数描述命题,或证据精确、不可驳斥及估计等信任程度,从不同角度刻划命题或证据的不精确性。
Fuzzy evidence (D-S) theory is based on nonempty sets. The membership function can be determined by comparison, increment, three division method or subjectiveness, then the function is tested by experiments. Basing on the information granularity and probability, the D-S theory is generalized to fuzzy sets. The expected certainty and expected probability are defined as generalized belief function and generalized plausibility function respectively. Belief function, plausibility function and genus probability function are adopted to depict the proposition. The proposition or evidence uncertainty is described in different aspects by the belief degree of estimation, un-rebut and conditional evidence.
出处
《兵工自动化》
2005年第3期79-81,共3页
Ordnance Industry Automation
关键词
模糊集
证据理论
不确定推理
模糊证据理论
Fuzzy sets
Evidence theory
Uncertainty reasoning
Fuzzy evidence theory
