Towards Learning in Grey Spatiotemporal Systems: A Prophet to Non-consecutive Spatiotemporal Dynamics. (arXiv:2208.08878v1 [cs.LG])

Spatiotemporal forecasting is an imperative topic in data science due to its
diverse and critical applications in smart cities. Existing works mostly
perform consecutive predictions of following steps with observations completely
and continuously obtained, where nearest observations can be exploited as key
knowledge for instantaneous status estimation. However, the practical issues of
early activity planning and sensor failures elicit a brand-new task, i.e.,
non-consecutive forecasting. In this paper, we define spatiotemporal learning
systems with missing observation as Grey Spatiotemporal Systems …

arxiv dynamics learning lg prophet systems