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Comparative Analysis of Bus Dwell Time Based on Time Series Methods

机译:基于时间序列方法的公交车停留时间比较分析

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This paper reports an investigation of short-term prediction of bus dwell time based on historical AVL data collected from selected bus stops in Auckland, New Zealand. Time series prediction based on gene expression programming (GEP) for the first time conducted at several different bus stops to model and estimate bus dwell time. Performance of the proposed GEP model compared to the well-known autoregressive integrated moving average (ARIMA) model. Three different methods including mean absolute error, root mean square error and mean absolute percentage error were used to assess the accuracy of the models. The GEP performed reasonably well for a short-term prediction of bus dwell time and gave comparable accuracy to the ARIMA Model.
机译:本文报告了根据从新西兰奥克兰的特定公交车站收集的历史AVL数据对公交车停留时间进行短期预测的调查。首次基于基因表达编程(GEP)的时间序列预测是在几个不同的公交车站进行的,以建模和估算公交的停留时间。与知名的自回归综合移动平均值(ARIMA)模型相比,所提出的GEP模型的性能。使用三种不同的方法(包括均值绝对误差,均方根误差和均值绝对百分比误差)来评估模型的准确性。 GEP对于公交车的停留时间的短期预测表现良好,并具有与ARIMA模型相当的准确性。

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