A comparative analysis of deep learning models for soil temperature prediction in cold climates
Author:
Funder
National Research Council Canada
Publisher
Springer Science and Business Media LLC
Subject
Atmospheric Science
Link
https://link.springer.com/content/pdf/10.1007/s00704-023-04781-x.pdf
Reference26 articles.
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2. Bayatvarkeshi M, Bhagat SK, Mohammadi K, Kisi O, Farahani M, Hasani A, Deo R, Yaseen ZM (2021) Modeling soil temperature using air temperature features in diverse climatic conditions with complementary machine learning models. Comput Electron Agric 185:106158. https://doi.org/10.1016/j.compag.2021.106158
3. Beck HE, Zimmermann NE, McVicar TR, Vergopolan N, Berg A, Wood EF (2018) Present and future Köppen-Geiger climate classification maps at 1-km resolution. Sci Data 5:180214. https://doi.org/10.1038/sdata.2018.214
4. Belouz K, Zereg S (2023) Extreme learning machine for soil temperature prediction using only air temperature as input. Environ Monit Assess 195(8):962. https://doi.org/10.1007/s10661-023-11566-2
5. Bonakdari H, Moeeni H, Ebtehaj I, Zeynoddin M, Mahoammadian A, Gharabaghi B (2019) New insights into soil temperature time series modeling: Linear or nonlinear? Arch Meteorol Geophys Bioclimatol Ser B 135:1157–1177
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