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fuzzy evidence
相关语句
  模糊证据
     Overview of Fuzzy Evidence Theory
     模糊证据理论综述
短句来源
     Fuzzy evidence (D-S) theory is based on nonempty sets.
     模糊证据(D-S)理论基于非空集合。
短句来源
     Fuzzy Evidence Theory and Its Application in Information Fusion
     模糊证据理论及其在信息融合中的应用
短句来源
     A New Interpretation of Fuzzy Evidence Theory
     关于模糊证据理论的一个新解释
短句来源
     The Extension of Fuzzy Evidence Theory and its Application in Reliability Assessment
     模糊证据理论的推广及其在产品可靠性评估中的应用
短句来源
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  “fuzzy evidence”译为未确定词的双语例句
     Indefinite Decision Making Based on Fuzzy Evidence
     基于模糊证据的不确定型决策
短句来源
  相似匹配句对
     Overview of Fuzzy Evidence Theory
     模糊证据理论综述
短句来源
     A New Interpretation of Fuzzy Evidence Theory
     关于模糊证据理论的一个新解释
短句来源
     M-N-Fuzzy Subgroup
     M-N-Fuzzy子群
短句来源
     On L Fuzzy Subgroups
     关于L-Fuzzy子群
短句来源
     On Hypnotic Evidence
     论催眠证据
短句来源
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  fuzzy evidence
Finally, an effective decision rule is developed to take into account uncertainty, quantified by Shannon entropy and fuzzy entropy, of probabilistic evidence and fuzzy evidence, to deal with conflict and to achieve robust decisions.
      
A generalized Dempster's rule is then utilized to combine fuzzy evidence structures associated with multiple information sources.
      
A new fuzzy evidence structure model is first introduced to formulate probabilistic evidence and fuzzy evidence in a unified framework.
      
We now show how to aggregate the fuzzy evidence when multiple rules make inferences about the same linguistic variable.
      
We will now discuss the case when fuzzy evidence must be propagated through multiple rules simultaneously and the results aggregated.
      
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The evidence combination problem in Dempster- Shafer's theory is studied in the paper. The including degree for the focal element of fuzzy evidence is defined. As an extension of Dempster's rule of combination, a new combination method for fuzzy evidence is put forward, thus the application fields of evidence theory are widened.

本文研究Dempster-Shafer理论中的证据合成问题。文中定义了模糊证据焦元的包含度,提出了一种模糊证据合成方法作为对Dempster合成规则的一个推广,从而拓宽了证据理论的应用范围。

This paper generalizes the concept of random sets presented by Dempster, and discusses the relationship between the uncertainty structure of fuzzy information sources and fuzzy event spaces. The paper also gives a kind of interpretation for the fuzzy evidence theory by the generalized concept of upper and lower probabilities. Meanwhile, it shows that the fuzzy conditioning belief function is, in fact, a generalization of Dempster's rule of fuzzy condition.

推广了Dempster所提出的随机集概念,并讨论了模糊信息源的不确定结构与模糊事件空间之间的关系,最后特别地用广义的上、下概率概念给出了模糊证据理论的一种新的解释,同时证明了模糊条件信任函数实际上是Dempster模糊条件规则的推广。

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...

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.

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。

 
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