Ditapis dengan
Pore-to-Darcy scale permeability upscaling for media with dynamic pore struct…
Permeability is a key rock property important for scientific applications that require simulation of fluid flow. Although permeability is determined using core flooding experiments, recent advancements in micro-CT imaging and pore scale fluid flow simulations have made it possible to constrain permeability honoring pore scale rock structure. Previous studies have reported that complex associati…
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 13 hlm PDF, 10.127 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
PixelSWAT: A user-friendly ArcGIS tool for preparing inputs to run SWAT in a …
This paper documents the development of PixelSWAT, a Graphical User interface (GUI) python toolbox developed with the motive of creating gridded watershed and stream features to run the Soil and Water Assessment Tool (SWAT) in a distributed discretization scheme thus allowing optimum utilization of gridded weather datasets. Additionally, the tool also aims to automate the preparation of SWAT we…
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 17 hlm PDF, 20.155 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Optimizing bathymetric position index (BPI) calculation: An analysis of param…
The present research paper addresses a critical gap in existing literature concerning the absence of a standardized methodology for parameter selection in the computation of the Bathymetric Position Index (BPI) values. The BPI is a measure of where a georeferenced location, with a defined depth, is relative to the neighbouring seascape, and it plays a significant role in characterizing benthic …
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 15 hlm PDF, 24.262 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Modeling river flow for flood forecasting: A case study on the Ter river
Floods affect chronically many communities around the world. Their socioeconomic impact increases year-by-year, boosted by global warming and climate change. Combined with long-term preemptive measures, preparatory actions are crucial when floods are imminent. In the last decade, machine learning models have been used to anticipate these hazards. In this work, we model the Ter river (NE Spain),…
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 12 hlm PDF, 2.425 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Machine Learning model interpretability using SHAP values: Application to Ign…
El Fierro intrusive body is one of the bodies that compose the La Jovita–Las Aguilas mafic–ultramafic belt, located in the Sierra Grande de San Luis, Argentina. The units of this belt carry a base metal sulfide (BMS) mineralization and platinum group minerals (PGM). The macroscopic description of mafic and ultramafic rocks, as is usually done by the mining exploration companies, leads to an…
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 9 hlm PDF, 2.393 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
LSTM-based DEM generation in riverine environment
In the broad field of sensors and 3D information retrieval, bathymetric reconstruction from side-scan sonar imaging is associated with unique technical hurdles. Neural Networks have recently led to promising new solutions in this field, but the available methods tend to be complex and data-intensive in a way typically making their use in a riverine environment impossible. Throughout our work, w…
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 9 hlm PDF, 4.631 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Long-term temperature prediction with hybrid autoencoder algorithms
This paper proposes two hybrid approaches based on Autoencoders (AEs) for long-term temperature prediction. The first algorithm comprises an AE trained to learn temperature patterns, which is then linked to a second AE, used to detect possible anomalies and provide a final temperature prediction. The second proposed approach involves training an AE and then using the resulting latent space as i…
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 13 hlm PDF, 1.864 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Interpretation techniques to explain the output of a spatial land subsidence …
Due to the nature of black-box machine learning (ML) models used in the spatial modelling field of environmental and natural hazards, the interpretation of predictive model outputs is necessary. For this purpose, we applied four interpretation techniques consisting of interaction plot, permutation feature importance (PFI) measure, shapley additive explanation (SHAP) decision plot, and accumulat…
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 12 hlm PDF, 15.238 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Improved reservoir characterization of thin beds by advanced deep learning ap…
Targeting reservoirs below seismic resolution presents a major challenge in reservoir characterization. High-resolution seismic data is critical for imaging the thin gas-bearing Khadro sand facies in several fields within the Lower Indus Basin (LIB). To truly characterize thin beds below tuning thickness, we showcase an optimally developed deep learning technique that can save up to 75% turn-ar…
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 12 hlm PDF, 15.238 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Global Normalized Difference Vegetation Index forecasting from air temperatur…
The complexity of the relationship between climate variables including temperature, precipitation, soil moisture, and the Normalized Difference Vegetation Index (NDVI) arises from the complex interaction between these factors. NDVI is a widely used index to analyze the characteristics of vegetation cover, including its dynamic patterns. It is a crucial parameter for examining vegetation stabili…
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 11 hlm PDF, 6.026 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
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