What is it about?
Optimal routing algorithms can improve the efficiency of public transport, reduce costs, and prevent accidents in road networks. This paper is a step forward in that direction. Specifically, we propose a new deep-learning model to impute stochastic missing values in a road network.
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Why is it important?
We propose the first model that can learn spatio-temporal correlations to impute stochastic missing values. The techniques implemented show that it is possible to accurately estimate the missing values of a road network in a reasonable amount of time.
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This page is a summary of: Spatio-temporal graph convolutional network for stochastic traffic speed imputation, November 2022, ACM (Association for Computing Machinery),
DOI: 10.1145/3557915.3560948.
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