实时旅行者信息的数据处理技术:在郊区干线上使用专用短程通信探头

Q3 Social Sciences
Jinhwan Jang
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引用次数: 0

摘要

在本研究中,提出了解决这两个问题的数据处理方法。在研究了测试段上行程时间的特征后,建议使用修正的z分数来审查包含在探针行程时间中的异常值。为了缓解时滞现象,将递归神经网络(一类通常处理时间序列数据的深度学习)应用于预测旅行时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Processing Techniques for Real-Time Traveler Information: Use of Dedicated Short-Range Communications Probes on Suburban Arterial
In this study, data processing methods for addressing the two issues are proposed. After investigating the characteristic of the travel times on the test section, the modified z-score was suggested for censoring outliers contained in probe travel times. To mitigate the time-lag phenomenon, a recurrent neural network, a class of deep learning where temporal sequence data are normally treated, was applied to predict travel times.
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来源期刊
Open Transportation Journal
Open Transportation Journal Social Sciences-Transportation
CiteScore
2.10
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0.00%
发文量
19
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