[HTML][HTML] A survey of traffic prediction: from spatio-temporal data to intelligent transportation
Intelligent transportation (eg, intelligent traffic light) makes our travel more convenient and
efficient. With the development of mobile Internet and position technologies, it is reasonable …
efficient. With the development of mobile Internet and position technologies, it is reasonable …
Urban big data fusion based on deep learning: An overview
Urban big data fusion creates huge values for urban computing in solving urban problems.
In recent years, various models and algorithms based on deep learning have been …
In recent years, various models and algorithms based on deep learning have been …
Exploiting dynamic spatio-temporal graph convolutional neural networks for citywide traffic flows prediction
The prediction of crowd flows is an important urban computing issue whose purpose is to
predict the future number of incoming and outgoing people in regions. Measuring the …
predict the future number of incoming and outgoing people in regions. Measuring the …
Exploiting dynamic spatio-temporal correlations for citywide traffic flow prediction using attention based neural networks
For intelligent transportation systems (ITS), predicting urban traffic crowd flows is of great
importance. However, it is challenging to represent various complex spatial relationships …
importance. However, it is challenging to represent various complex spatial relationships …
Spatiotemporal multi-graph convolution network for ride-hailing demand forecasting
Region-level demand forecasting is an essential task in ridehailing services. Accurate ride-
hailing demand forecasting can guide vehicle dispatching, improve vehicle utilization …
hailing demand forecasting can guide vehicle dispatching, improve vehicle utilization …
Bitcoin price prediction using machine learning: An approach to sample dimension engineering
Z Chen, C Li, W Sun - Journal of Computational and Applied Mathematics, 2020 - Elsevier
After the boom and bust of cryptocurrencies' prices in recent years, Bitcoin has been
increasingly regarded as an investment asset. Because of its highly volatile nature, there is a …
increasingly regarded as an investment asset. Because of its highly volatile nature, there is a …
A data aggregation based approach to exploit dynamic spatio-temporal correlations for citywide crowd flows prediction in fog computing
Accurate and timely predicting citywide traffic crowd flows precisely is crucial for public
safety and traffic management in smart cities. Nevertheless, its crucial challenge lies in how …
safety and traffic management in smart cities. Nevertheless, its crucial challenge lies in how …
Revisiting spatial-temporal similarity: A deep learning framework for traffic prediction
Traffic prediction has drawn increasing attention in AI research field due to the increasing
availability of large-scale traffic data and its importance in the real world. For example, an …
availability of large-scale traffic data and its importance in the real world. For example, an …
Deep multi-view spatial-temporal network for taxi demand prediction
Taxi demand prediction is an important building block to enabling intelligent transportation
systems in a smart city. An accurate prediction model can help the city pre-allocate …
systems in a smart city. An accurate prediction model can help the city pre-allocate …