LEARNING SPATIOTEMPORAL FEATURES FROM INCOMPLETE DATA FOR TRAFFIC FLOW PREDICTION USING HYBRID DEEP NEURAL NETWORKS

被引：0
|
作者：
Ghazi, Mehdi Mehdipour [1 ]
Ramezani, Amin [2 ]
Siahi, Mehdi [1 ]
Ghazi, Mostafa Mehdipour [3 ]
机构：
[1] Faculty of Mechanics, Electrical and Computer Science, Research Branch IAU, Tehran, Iran
[2] Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran
[3] Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
来源：
arXiv | 2022年
关键词：
Convolutional neural network - Deep learning - Hybrid deep neural network - Hybrid network - Imputation techniques - Missing data imputations - Missing values - Performance measurement system - Traffic flow - Traffic flow prediction;
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