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Semantic Kriging for Spatio-temporal Prediction

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Semantic Kriging for Spatio-temporal Prediction/ by Shrutilipi Bhattacharjee, Soumya Kanti Ghosh, Jia Chen.
Author:	Bhattacharjee, Shrutilipi.
other author:	Ghosh, Soumya Kanti.
Description:	XXV, 127 p. 92 illus., 76 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computational intelligence. -
Online resource:	https://doi.org/10.1007/978-981-13-8664-0
ISBN:	9789811386640

Semantic Kriging for Spatio-temporal Prediction
Bhattacharjee, Shrutilipi.

Semantic Kriging for Spatio-temporal Prediction[electronic resource] /by Shrutilipi Bhattacharjee, Soumya Kanti Ghosh, Jia Chen. - 1st ed. 2019. - XXV, 127 p. 92 illus., 76 illus. in color.online resource. - Studies in Computational Intelligence,8391860-949X ;. - Studies in Computational Intelligence,564.

Chapter 1. Introduction -- Chapter 2. Spatial Interpolation -- Chapter 3. Spatial Semantic Kriging -- Chapter 4. Fuzzy Bayesian Semantic Kriging -- Chapter 5. Spatio-temporal Reverse Semantic Kriging -- Chapter 6. Summary and Future Research.

This book identifies the need for modeling auxiliary knowledge of the terrain to enhance the prediction accuracy of meteorological parameters. The spatial and spatio-temporal prediction of these parameters are important for the scientific community, and the semantic kriging (SemK) and its variants facilitate different types of prediction and forecasting, such as spatial and spatio-temporal, a-priori and a-posterior, univariate and multivariate. As such, the book also covers the process of deriving the meteorological parameters from raw satellite remote sensing imagery, and helps understanding different prediction method categories and the relation between spatial interpolation methods and other prediction methods. The book is a valuable resource for researchers working in the area of prediction of meteorological parameters, semantic analysis (ontology-based reasoning) of the terrain, and improving predictions using auxiliary knowledge of the terrain.

ISBN: 9789811386640

Standard No.: 10.1007/978-981-13-8664-0doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Semantic Kriging for Spatio-temporal Prediction
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