组合概率诊断熵与信息
A Combinatorial-Probabilistic Diagnostic Entropy and Information
摘要：
提出了一种新的组合概率诊断熵。它描述了在诊断过程中必须区分的系统条件的概率的成对和。该方法描述了系统状态的不确定性，同时也描述了诊断问题的时间复杂度。治疗假设的组合诊断熵作为一个主要的概念，由症状提供的信息已被定义。的关系已被推导出，以方便明确的，定量评估的信息，一个单一的症状，以及症状集。证明了组合概率信息具有可加性。所提出的措施集中在诊断问题，但他们可以很容易地应用到其他学科，如决策理论和分类。
英文摘要：
A new combinatorial-probabilistic diagnostic entropy has been introduced. It describes the pair-wise sum of probabilities of system conditions that have to be distinguished during the diagnosing process. The proposed measure describes the uncertainty of the system conditions, and at the same time complexity of the diagnosis problem. Treating the assumed combinatorial-diagnostic entropy as a primary notion, the information delivered by the symptoms has been defined. The relationships have been derived to facilitate explicit, quantitative assessment of the information of a single symptom as well as that of a symptoms set. It has been proved that the combinatorial-probabilistic information shows the property of additivity. The presented measures are focused on diagnosis problem, but they can be easily applied to other disciplines such as decision theory and classification.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
