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Interruption Risk Assessment and Transmission of Fresh Cold Chain Network Based on a Fuzzy Bayesian Network

机译:基于模糊贝叶斯网络的新冷链网络中断风险评估与传输

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The fresh cold chain network is complex, and the interruption risk can significantly impact it. Based on the Bayesian theory, we constructed a fresh cold chain network interruption risk topology structure. The probability of each root node was predicted and calculated based on the fuzzy set theory. The evaluation model was then validated and improved through the virus transmission model based on risk transmission. Sensitivity analysis was used to determine significant risk factors. Several strategies for minimizing interruption risks were identified.
机译:新鲜的冷链网络是复杂的,中断风险可以显着影响它。 基于贝叶斯理论,我们构建了一种新的冷链网络中断风险拓扑结构。 基于模糊集理论预测和计算每个根节点的概率。 然后通过基于风险传输通过病毒传输模型进行验证和改善评估模型。 敏感性分析用于确定显着的风险因素。 确定了最大限度地减少中断风险的几种策略。

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