Spatiotemporal forecasting has various applications in neuroscience, climate and transportation domain.
#3 best model for Traffic Prediction on PeMS-M
The paper presents a spatio-temporal wind speed forecasting algorithm using Deep Learning (DL)and in particular, Recurrent Neural Networks(RNNs).
This task is challenging due to the complicated spatiotemporal dependencies among regions.
Integro-difference equation (IDE) models describe the conditional dependence between the spatial process at a future time point and the process at the present time point through an integral operator.