UID:
almahu_9948126380602882
Format:
XXV, 127 p. 92 illus., 76 illus. in color.
,
online resource.
Edition:
1st ed. 2019.
ISBN:
9789811386640
Series Statement:
Studies in Computational Intelligence, 839
Content:
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.
Note:
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.
In:
Springer eBooks
Additional Edition:
Printed edition: ISBN 9789811386633
Additional Edition:
Printed edition: ISBN 9789811386657
Additional Edition:
Printed edition: ISBN 9789811386664
Language:
English
DOI:
10.1007/978-981-13-8664-0
URL:
https://doi.org/10.1007/978-981-13-8664-0
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