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提出一种基于因果网络的诊断推理模型.该模型用因果网络表示诊断对象的领域知识,不仅能有效地表达知识的不确定性,更重要的是解决了知识的不完备问题.该模型的推理过程分为领域相关的环境集识别和领域无关的诊断解产生两个阶段,增加了算法的柔性和通用性.
This paper proposes a diagnosis reasoning model based on causal network.This model uses the causal network to represent the domain knowledge of diagnostic objects, which can not only effectively express the uncertainty of knowledge, but more importantly, solve the problem of incomplete knowledge.The reasoning of the model The process is divided into two stages, that is, field-related environment set identification and domain-independent diagnostic solution, which increases the flexibility and universality of the algorithm.