关键词: 贝叶斯网络, 相对推断, 专家推断, 推断信息约简, 条件概率表

Abstract: In order to solve the problem of lacking effectiveness in the individuals inference and scientific in the overall integration results, which existed in the conditional probability tables in Bayesian network according to experts knowledge inference, the inferred information reduction mechanism is proposed to make judgment objects more intuitive and judgment modes more simple. Then the pair-wised judgment matrix in the Analytic Hierarchy Process（AHP） is used as an extraction means and information carriers of the subjective conditional probability. After that, the experts relative inference method for deriving optimal conditional probability from macro and micro information is constructed, the proposed method on one hand can overcome the problem of lacking effectiveness in individual inferred information caused by experts’ limited concluding ability in the traditional method, on the other hand it is possible to make effective comprehensive integration of experts’ inferred information to ensure scientific of the results. Then the construction process of Bayesian networks is proposed following an inference sequence of “anterior to later”. Finally a data comparison analysis and a case simulation analysis are employed to prove the present method to be scientific, applicable and feasible.

Key words: Bayesian network, relative inference, expert inference, inferred information reduction, conditional probability table