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Spatial Time Series Prediction Using Advanced BN Models—An Application Perspective

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Book cover Enhanced Bayesian Network Models for Spatial Time Series Prediction

Part of the book series: Studies in Computational Intelligence ((SCI,volume 858))

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Abstract

While the previous chapters keep focus on the working principles and performances of variants of enhanced BN models, this chapter presents the BN models from the perspective of various applications of spatial time series  prediction. Eight different application domains including medical imaging, remote sensing , transportation, bio-informatics, homeland security, environment/ecology, finance/economy, etc. have been considered for this purpose. Later, the chapter also discusses on the synergism of enhanced BN models to handle more complex ST prediction scenarios in real life. We anticipate that the chapter will help researchers to find out several interesting research issues yet to be resolved and will also encourage them to further explore the intrinsic power of BNs to tackle the same.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India

    Monidipa Das & Soumya K. Ghosh

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  1. Monidipa Das
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Correspondence to Monidipa Das .

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Das, M., Ghosh, S.K. (2020). Spatial Time Series Prediction Using Advanced BN Models—An Application Perspective. In: Enhanced Bayesian Network Models for Spatial Time Series Prediction. Studies in Computational Intelligence, vol 858. Springer, Cham. https://doi.org/10.1007/978-3-030-27749-9_8

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