| 书目名称 | Semantic Kriging for Spatio-temporal Prediction |
| 编辑 | Shrutilipi Bhattacharjee,Soumya Kanti Ghosh,Jia Ch |
| 视频video | |
| 概述 | Identifies the need for modeling auxiliary knowledge of the terrain to enhance the prediction accuracy.Discusses novel semantic kriging (SemK) and its variants, which facilitate different types of pre |
| 丛书名称 | Studies in Computational Intelligence |
| 图书封面 |  |
| 描述 | .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.. |
| 出版日期 | Book 2019 |
| 关键词 | GeoScience; Remote Sensing; Meteorological Parameters; Spatio-temporal Data; Prediction; Kriging; Semantic |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-981-13-8664-0 |
| isbn_softcover | 978-981-13-8666-4 |
| isbn_ebook | 978-981-13-8664-0Series ISSN 1860-949X Series E-ISSN 1860-9503 |
| issn_series | 1860-949X |
| copyright | Springer Nature Singapore Pte Ltd. 2019 |
发表于 2025-3-21 16:13:38
