Aiming at the prediction problem of transport capacity risk caused by the mismatch between the carrying capacity of rail transit network and passenger flow demand, this paper proposes an explainable prediction method of rail transit network transport capacity risk based on linear Gaussian Bayesian network. This method obtains the training data of the prediction model based on the simulation model of the rail transit system with a three-layer structure including rail transit network, train flow and passenger flow. A Bayesian network structure construction method based on the topology of the rail transit network is proposed, and the MLE (Maximum Likelihood Estimation) method is used to realize the parameter learning of the Bayesian network. Finally, the effectiveness of the proposed method is verified by simulation examples.

翻译：针对轨道交通网络承载能力与客流需求不匹配导致的运输能力风险预测问题，本文提出一种基于线性高斯贝叶斯网络的轨道交通网络运输能力可解释预测方法。该方法通过包含轨道交通网络、列车流和客流三层结构的轨道交通系统仿真模型获取预测模型的训练数据，提出基于轨道交通网络拓扑结构的贝叶斯网络结构构建方法，并采用极大似然估计法实现贝叶斯网络的参数学习。最后通过仿真算例验证了所提方法的有效性。