Enhanced Bayesian network models for spatial time series prediction : recent research trend in data-driven predictive analytics

Author(s)

    • Das, Monidipa
    • Ghosh, Soumya K.

Bibliographic Information

Enhanced Bayesian network models for spatial time series prediction : recent research trend in data-driven predictive analytics

Monidipa Das, Soumya K. Ghosh

(Studies in computational intelligence, v. 858)

Springer, c2020

Available at  / 2 libraries

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Note

Includes bibliographical references and index

Description and Table of Contents

Description

This research monograph is highly contextual in the present era of spatial/spatio-temporal data explosion. The overall text contains many interesting results that are worth applying in practice, while it is also a source of intriguing and motivating questions for advanced research on spatial data science. The monograph is primarily prepared for graduate students of Computer Science, who wish to employ probabilistic graphical models, especially Bayesian networks (BNs), for applied research on spatial/spatio-temporal data. Students of any other discipline of engineering, science, and technology, will also find this monograph useful. Research students looking for a suitable problem for their MS or PhD thesis will also find this monograph beneficial. The open research problems as discussed with sufficient references in Chapter-8 and Chapter-9 can immensely help graduate researchers to identify topics of their own choice. The various illustrations and proofs presented throughout the monograph may help them to better understand the working principles of the models. The present monograph, containing sufficient description of the parameter learning and inference generation process for each enhanced BN model, can also serve as an algorithmic cookbook for the relevant system developers.

Table of Contents

Introduction.- Standard Bayesian Network Models for Spatial Time Series Prediction.- Bayesian Network with added Residual Correction Mechanism.- Spatial Bayesian Network.- Semantic Bayesian Network.- Advanced Bayesian Network Models with Fuzzy Extension.- Comparative Study of Parameter Learning Complexity.- Spatial Time Series Prediction using Advanced BN Models- An Application Perspective.- Summary and Future Research.

by "Nielsen BookData"

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Details

  • NCID
    BB29326805
  • ISBN
    • 9783030277482
  • Country Code
    sz
  • Title Language Code
    eng
  • Text Language Code
    eng
  • Place of Publication
    Cham
  • Pages/Volumes
    xxiii, 149 p.
  • Size
    25 cm
  • Parent Bibliography ID
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