Spatio-Temporal Prediction of Meteorological Time Series Data: An Approach Based on Spatial Bayesian Network (SpaBN)

This paper proposes a space-time model for prediction of meteorological time series data. The proposed prediction model is based on a spatially extended Bayesian network (SpaBN), which helps to efficiently model the complex spatio-temporal dependency among large number of spatially distributed variables. Validation has been made with respect to prediction of daily temperature, humidity, and precipitation rate around the spatial region of Kolkata, India. Comparative study with the benchmark and state-of-the-art prediction techniques demonstrates the superiority of the proposed spatio-temporal prediction model.