Mar 5, 2020 · Abstract: In this paper, we study the prediction of traffic flow in the presence of missing information from data set.
We developed an algorithm for efficient realization of deep learning for traffic data imputation by training the model hierarchically using the full set of ...
Mar 15, 2020 · PDF | In this paper, we study the prediction of traffic flow in the presence of missing information from data set.
Mar 17, 2020 · The experiments demonstrate the effectiveness of using deep learning based imputation in improving the accuracy of traffic flow prediction.
We further investigated why the deep leaning model works well for traffic data imputation by visualizing the features extracted by the first hidden layer.
Online data imputation and traffic prediction based on real-time data streams are essential for the intelligent transportation systems, particularly online ...
Nov 21, 2016 · Through these experiments and evaluation results, the authors developed an algorithm for efficient realization of deep learning for traffic data ...
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The model denoising stacked autoencoders for traffic data imputation is proposed. The model performance changes with temporal and spatial factors.
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This paper proposes an approach based on deep learning to impute the missing traffic data and shows that the proposed approach can keep a stable error under ...
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Feb 16, 2024 · In this paper, we introduce a model called Traffic Data Imputation (TDI) specifically designed to address missing values in traffic data.