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SVM based multi-index evaluation for bus arrival time prediction

机译:基于SVM的公交车站到站时间多指标评估

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The real time prediction of bus arrival time is important in public transport service. Many researches use a traditional error metrics to measure the predicting accuracy, which cannot evaluate the prediction service comprehensively. This paper proposes a novel multi-index evaluation method based on Support Vector Machine (SVM) for bus arrival time prediction. This method uses three new indexes including GPS coverage, release rate, and accuracy rate to evaluate the prediction service, and then uses SVM to train the model for multi-index evaluation. Experiment results show that our method is intuitive and comprehensive by using SVM based multi-index evaluation, and can position issue accurately according to the three new indexes.
机译:公交车到站时间的实时预测在公共交通服务中很重要。许多研究使用传统的误差度量来度量预测准确性,但无法全面评估预测服务。提出了一种基于支持向量机(SVM)的公交车到达时间预测的多指标评估方法。该方法使用GPS覆盖率,释放率和准确率这三个新指标来评估预测服务,然后使用SVM训练模型以进行多指标评估。实验结果表明,采用基于支持向量机的多指标评估方法,该方法直观,综合,可以根据三个新指标准确定位问题。

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