Locally varying geostatistical machine learning for spatial prediction
Machine learning methods dealing with the spatial auto-correlation of the response variable have garnered significant attention in the context of spatial prediction. Nonetheless, under these method…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 18 hlm PDF, 9.301 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Automated stratigraphic correlation of well logs using Attention Based Dense …
The stratigraphic correlation of well logs plays an essential role in characterizing subsurface reservoirs. However, it suffers from a small amount of training data and expensive computing time. In…
- Edisi
- Vol.4, December 2023
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 9 hlm PDF, 4.161 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Using a 3D heat map to explore the diverse correlations among elements and mi…
This paper presents an enhanced 3D heat map for exploratory data analysis (EDA) of open mineral data, addressing the challenges caused by rapidly evolving datasets and ensuring scientifically meani…
- Edisi
- Vol.21, March 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 10 hlm PDF, 5.984 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Geotechnical soil mapping from electrical and mechanical properties: Case stu…
Preliminary work in civil engineering works often involves the investigation of soil support in order to secure or predict project safety. The objective of this work is to purpose an urban geotechn…
- Edisi
- Vol.13, March 2022
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 16 hlm PDF, 30.776 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
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