Ditapis dengan
Comparison of Backprojection Techniques for Rupture Propagation Modelling of …
This paper utilises teleseismic Z-component data to investigate rupture propagation, extent, and velocity for two very destructive earthquakes in the East Anatolian Fault Zone (EAFZ): the ???????? = 7.8 earthquake near Kahramanmaras and the largest (???????? = 7.5 s) aftershock at Elbistan (both on 6 February 2023). The extent of the rupture is modelled with beamforming and multichannel sig…
- Edisi
- Vol.15, Issue 4, April 2025
- ISBN/ISSN
- 2076-3263
- Deskripsi Fisik
- 19 hlm PDF, 1.744 KB
- Judul Seri
- Geosciences
- No. Panggil
- 550
Optimized Random Forest Models for Rock Mass Classification in Tunnel Constru…
The accurate prediction of rock mass quality ahead of the tunnel face is crucial for optimizing tunnel construction strategies, enhancing safety, and reducing geological risks. This study developed three hybrid models using random forest (RF) optimized by moth-flame optimization (MFO), gray wolf optimizer (GWO), and Bayesian optimization (BO) algorithms to classify the surrounding rock in real …
- Edisi
- Vol.15, Issue 2, February 2025
- ISBN/ISSN
- 2076-3263
- Deskripsi Fisik
- 26 hlm PDF, 3.524 KB
- Judul Seri
- Geosciences
- No. Panggil
- 550
Contribution of multispectral (optical and radar) satellite images to the cla…
The monitoring of different crops (cultivated plots) and types of surface (bare soils, etc.) is a crucial economic and environmental issue for the management of resources and human activity. In this context, the objective of this study is to evaluate the contribution of multispectral satellite imagery (optical and radar) to land use and land cover classification. Object-oriented supervised cla…
- Edisi
- Vol.84, February 2020
- ISBN/ISSN
- 1569-8432
- Deskripsi Fisik
- 13 hlm PDF, 5.659 KB
- Judul Seri
- International Journal of Applied Earth Observation and Geoinformation - Open Access
- No. Panggil
- 910.285
Reconstruction of lithofacies using a supervised Self-Organizing Map: Applica…
Recently, machine learning (ML) has been considered a powerful technological element of different society areas. To transform the computer into a decision maker, several sophisticated methods and algorithms are constantly created and analyzed. In geophysics, both supervised and unsupervised ML methods have dramatically contributed to the development of seismic and well-log data interpretation. …
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 13 hlm PDF, 3.426 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Pore size classification and prediction based on distribution of reservoir fl…
Pore size analysis plays a pivotal role in unraveling reservoir behavior and its intricate relationship with confined fluids. Traditional methods for predicting pore size distribution (PSD), relying on drilling cores or thin sections, face limitations associated with depth specificity. In this study, we introduce an innovative framework that leverages nuclear magnetic resonance (NMR) log data, …
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 23 hlm PDF, 24.240 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Enhancing economic sustainability in mature oil fields: Insights from the clu…
Fluctuations in oil prices adversely affect decision making situations in which performance forecasting must be combined with realistic price forecasts. In periods of significant price drops, companies may consider extended duration of well shut-ins (i.e. temporarily stopping oil production) for economic reasons. For example, prices during the early days of the Covid-19 pandemic forced operator…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 16 hlm PDF, 1.767 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Toward earthquake early warning: A convolutional neural network for rapid ear…
Earthquake early warning (EEW) is one of the important tools to reduce the hazard of earthquakes. In contemporary seismology, EEW is typically transformed into a fast classification of earthquake magnitude, i.e., large magnitude earthquakes that require warning are in the positive category and vice versa in the negative category. However, the current standard information signal processing routi…
- Edisi
- Vol.4, December 2023
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 8 hlm PDF, 5.714 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Classification random forest with exact conditioning for spatial prediction o…
Machine learning methods are increasingly used for spatially predicting a categorical target variable when spatially exhaustive predictor variables are available within the study region. Even though these methods exhibit competitive spatial prediction performance, they do not exactly honor the categorical target variable's observed values at sampling locations by construction. On the other side…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 14 hlm PDF, 7.744 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Capsule network-based approach for estimating grassland coverage using time s…
The degradation and desertification of grasslands pose a daunting challenge to China's arid and semiarid areas owing to the increasing demand for them in light of the rise of animal husbandry. Monitoring grasslands by using big data has emerged as a popular area of research in recent years. As grassland degradation is a slow and gradual process, the accurate identification of grassland cover is…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 9 hlm PDF, 3,657 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Classification of geological borehole descriptions using a domain adapted lar…
Geological borehole descriptions contain detailed textual information about the composition of the subsurface. However, their unstructured format presents significant challenges for extracting relevant features into a structured format. This paper introduces GEOBERTje: a domain adapted large language model trained on geological borehole descriptions from Flanders (Belgium) in the Dutch language…
- Edisi
- Vol.25, February 2025
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 15 hlm PDF, 2.295 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
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