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Ditemukan 3 dari pencarian Anda melalui kata kunci: subject="Frost"
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Applying Data Analysis and Machine Learning Methods to Predict Permafrost Coa…
Komentar Bagikan
Daria BogatovaStanislav Ogorodov

This study aims to establish a scientific and methodological basis for predicting shoreline positions using modern data analysis and machine learning techniques. The focus area is a 5 km section of the Ural coast along Baydaratskaya Bay in the Kara Sea. This region was selected due to its diverse geomorphological features, varied lithological composition, and significant presence of permafrost …

Edisi
Vol.15, Issue 1, January 2025
ISBN/ISSN
2076-3263
Deskripsi Fisik
19 hlm PDF, 2.124 KB
Judul Seri
Geosciences
No. Panggil
550
cover
Improved frost forecast using machine learning methods
Komentar Bagikan
Jose Roberto RozanteEnver RamirezDiego RamirezGabriela Rozante

Frosts are one of the atmospheric phenomena with one of the larger negative effects on the agricultural sector in the southern region of Brazil, therefore, an earlier forecast can minimize their impacts. In the present work, artificial neural networks (ANNs) techniques were applied in order to improve the predicting capabilities of frost events in southern Brazil. In the study, two multilayer p…

Edisi
Vol.4, December 2023
ISBN/ISSN
2666-5441
Deskripsi Fisik
18 hlm PDF, 19.643 KB
Judul Seri
Artificial Intelligence in Geosciences
No. Panggil
551
cover
Machine learning – An approach for consistent rock glacier mapping and inve…
Komentar Bagikan
Georg H. ErharterThomas WagnerGerfried WinklerThomas Marcher

Rock glaciers (RG) are landforms that occur in high latitudes or elevations and — in their active state — consist of a mixture of rock debris and ice. Despite serving as a form of groundwater storage, they are an indicator for the occurrence of (former) permafrost and therefore carry significance in the research for the ongoing climate change. For these reasons, the past years have shown ri…

Edisi
Vol.16, December 2022
ISBN/ISSN
2590-1974
Deskripsi Fisik
12 hlm PDF, 13.829 KB
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136