DKNN: deep kriging neural network for interpretable geospatial interpolation-Reference-Cited by-同舟云学术

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DKNN: deep kriging neural network for interpretable geospatial interpolation

Published:2024-05-06 Issue:8 Volume:38 Page:1486-1530
ISSN:1365-8816
Container-title:International Journal of Geographical Information Science
language:en
Short-container-title:International Journal of Geographical Information Science

Author:

Chen Kaiqi¹^ORCID,Liu Enbo¹^ORCID,Deng Min¹²,Tan Xiaoyong¹,Wang Jiaoju³,Shi Yan¹^ORCID,Wang Zhizhong³

Affiliation:

1. School of Geosciences and Info-Physics, Central South University (CSU), Changsha, PR China

2. Hunan Geospatial Information Engineering and Technology Research Center, Changsha, PR China

3. School of Mathematics and Statistics, Central South University (CSU), Changsha, PR China

Funder

National Natural Science Foundation of China

Hunan Provincial Innovation Foundation for Postgraduates

Central South University Innovation-Driven Research Programme

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/13658816.2024.2347316

Reference97 articles.

1. Al-Kababji A. Bensaali F. and Dakua S.P. 2022. Scheduling techniques for liver segmentation: Reducelronplateau vs onecyclelr. In: A. Bennour ed. Intelligent systems and pattern recognition. Cham: Springer 204–212.

2. Kriging Convolutional Networks

3. Disjunctive kriging revisited: Part I

4. Spatio-Temporal Data Mining

5. A study of K-nearest neighbour as an imputation method;Batista G.E.;His,2002

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