An efficient realization of deep learning for traffic data imputation

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An efficient realization of deep learning for traffic data imputation

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作者：Yanjie Duan ^{duanyanjie2012@ia.ac.cn" class="auth_mail" title="E-mail the corresponding author} ; Yisheng Lv ; ^{yisheng.lv@ia.ac.cn" class="auth_mail" title="E-mail the corresponding author} ; Yu-Liang Liu ^{liuyuliangxp@126.com" class="auth_mail" title="E-mail the corresponding author} ; Fei-Yue Wang ^{feiyue@ieee.org" class="auth_mail" title="E-mail the corresponding author}
关键词：Traffic data imputation ; Deep learning ; Missing data
刊名：Transportation Research Part C: Emerging Technologies
出版年：2016
出版时间：November 2016
年：2016
卷：72
期：Complete
页码：168-181
全文大小：824 K

文摘

•: The model denoising stacked autoencoders for traffic data imputation is proposed.
•: The model performance changes with temporal and spatial factors.
•: An efficient model realization with hierarchically training algorithm is developed.

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