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Optimization of Rail Transit Departure Frequency Based on Fuzzy Clustering - Take Shanghai Rail Transit Line 9 for Example

机译:基于模糊聚类的轨道交通发车频率优化-以上海轨道交通9号线为例

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摘要

This article takes example of Shanghai Rail Transit Line 9, and uses fuzzy clustering method to classify passenger flow in different periods of the working and non-working days by MATLAB program. Full-day time intervals are divided into five categories, and we optimize the departure frequency based on the five categories. This optimization method improves the operational efficiency of urban railway transport, and reduces the cost of it. The method of research is innovative, and research findings are instructive in practice.
机译:本文以上海轨道交通9号线为例,通过模糊聚类方法,通过MATLAB程序对工作日和非工作日不同时段的客流进行分类。全天时间间隔分为五类,我们根据这五类优化出发频率。这种优化方法提高了城市铁路运输的运营效率,并降低了成本。研究方法是创新的,研究发现对实践具有指导意义。

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