基于PageRank的交路选择算法研究

Study on Route Selection Algorithm Based on PageRank

交路设计是行车计划编制中的重要考虑因素。本文通过对信号系统设备布置结构和设备属性的分析,以静态配置数据的形式表达分析结果,采用图机器学习方法建立用于交路选择的图模型。基于PageRank算法,对图模型中的节点进行重要度分析,给出了节点的重要度排序。依据节点的重要度和交路结构,实现了交路分类,给出了一种交路选择算法,为轨道交路选择提供了一种参考方案。最后,以某线路为例进行了实验验证。结果表明,算法可以有效提高交路选择效率。

Route design is a critical consideration in the compilation of rail operating schedules.This study analyzed the arrangement structure and attributes of signaling system equipment,and expressed the findings in the form of static configuration data.A graph model for rail route selection was established using graph machine learning methods.Applying the PageRank algorithm to the graph model,the importance of nodes was analyzed,yielding a ranked list of node significance.Based on node importance and route structure,a route classification was achieved,leading to the formulation of a route selection algorithm.This offers a reference solution for route selection.Then one line was taken as an example to validate the proposed algorithm,demonstrating its effectiveness in enhancing route selection efficiency.