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Semantic kriging for spatio-temporal...

Bhattacharjee, Shrutilipi.

Semantic kriging for spatio-temporal prediction

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Semantic kriging for spatio-temporal predictionby Shrutilipi Bhattacharjee, Soumya Kanti Ghosh, Jia Chen.
作者:	Bhattacharjee, Shrutilipi.
其他作者:	Ghosh, Soumya Kanti.
出版者:	Singapore :Springer Singapore :2019.
面頁冊數:	xxv, 127 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	MeteorologyMathematical models.
電子資源:	https://doi.org/10.1007/978-981-13-8664-0
ISBN:	9789811386640$q(electronic bk.)

Semantic kriging for spatio-temporal prediction
Bhattacharjee, Shrutilipi.

Semantic kriging for spatio-temporal prediction[electronic resource] /by Shrutilipi Bhattacharjee, Soumya Kanti Ghosh, Jia Chen. - Singapore :Springer Singapore :2019. - xxv, 127 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.8391860-949X ;. - Studies in computational intelligence ;v. 216..

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$q(electronic bk.)

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

510632
Meteorology
--Mathematical models.

LC Class. No.: QC866 / .B43 2019

Dewey Class. No.: 551.5028

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