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SVM based multi-index evaluation for bus arrival time prediction

机译:基于SVM的总线到达时间预测的多索引评估

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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:公共汽车到达时间的实时预测在公共交通服务中是重要的。许多研究使用传统的错误指标来测量预测准确性,这无法全面地评估预测服务。本文提出了一种基于支持向量机(SVM)的新型多指标评估方法,用于总线到达时间预测。该方法使用三个新索引,包括GPS覆盖率,释放率和准确率来评估预测服务,然后使用SVM培训模型进行多索引评估。实验结果表明,我们的方法是通过使用基于SVM的多索引评估的直观和全面,并且可以根据三个新索引准确定位问题。

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