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

  • Monidipa DasEmail author
  • Soumya K. Ghosh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10597)


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.


Space-time model Time series prediction Spatial Bayesian network Meteorology 


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringIndian Institute of Technology KharagpurKharagpurIndia

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