Semantic Kriging for Spatio-temporal Prediction

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 f...

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Detaylı Bibliyografya
Asıl Yazarlar: Bhattacharjee, Shrutilipi (Yazar), Ghosh, Soumya Kanti (Yazar), Chen, Jia (Yazar)
Müşterek Yazar: SpringerLink (Online service)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Singapore : Springer Nature Singapore : Imprint: Springer, 2019.
Edisyon:1st ed. 2019.
Seri Bilgileri:Studies in Computational Intelligence, 839
Konular:
Computational intelligence.
Geographic information systems.
Artificial intelligence.
Computational Intelligence.
Geographical Information System.
Artificial Intelligence.
Online Erişim:Full-text access
OPAC'ta görüntüle
İçindekiler:
  • 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.

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