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Standard Bayesian Network Models for Spatial Time Series Prediction

  • Monidipa DasEmail author
  • Soumya K. Ghosh
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 858)

Abstract

Bayesian networks (BNs) are one of the key computational models in traditional AI and machine learning  paradigm. These are also considered to belong to the probabilistic reasoning  family of computational intelligence  that forms the soft part of modern AI. In this chapter, we provide a preliminary idea on standard/classical Bayesian network, followed by its parameter learning and inference generation mechanism. We also cover the basic concepts of various categories of Bayesian networks , including dynamic Bayesian network, fuzzy Bayesian network, spatial Bayesian network, semantic Bayesian network etc. Further, we discuss on the potentials of BN in modeling the inter-variable dependencies while analyzing spatio-temporal data.

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

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

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