Ditapis dengan
Machine learning technique in the north zagros earthquake prediction
Studying the changes in seismicity, and the potential of the occurrences of large earthquakes in a seismic zone is not only extremely important from the aspect of seismological research, but it is additionally significant in the decisions of crisis management. Since, nowadays Machine learning techniques have proven the high ability for analyzing information, and discovering the relations among …
- Edisi
- Vol.22, June 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 9 hlm PDF, 2.915 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
GeoCoDA: Recognizing and validating structural processes in geochemical data.…
Geochemical data are compositional in nature and are subject to the problems typically associated with data that are restricted to the real non-negative number space with constant-sum constraint, that is, the simplex. Geochemistry can be considered a proxy for mineralogy, comprised of atomically ordered structures that define the placement and abundance of elements in the mineral lattice struct…
- Edisi
- Vol.22, June 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 15 hlm PDF, 1.985 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Parallel investigations of remote sensing and ground-truth Lake Chad’s leve…
Lake Chad is facing critical situations since the 1960s due to the effects of climate change and anthropogenic activities. The statistical analyses of remote sensing climate variables (i.e., evapotranspiration, specific humidity, soil temperature, air temperature, precipitation, soil moisture) and remote sensing and ground-truth lake level applied to the period 1993–2012 reveal that remote se…
- Edisi
- Vol.20, December 2023
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 16 hlm PDF, 8.082 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
AnnRG - An artificial neural network solute geothermometer
Solute artificial neural network geothermometers offer the possibility to overcome the complexity given by the solute-mineral composition. Herein, we present a new concept, trained from high-quality hydrochemical data and verified by in-situ temperature measurements with a total of 208 data pairs of geochemical input parameters (Na+, K+, Ca2+, Mg2+, Cl−, SiO2, and pH) and reservoir temperatur…
- Edisi
- Vol.20, December 2023
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 10 hlm PDF, 4.961 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
A practical approach for discriminating tectonic settings of basaltic rocks u…
Elucidating the tectonic setting of unknown rock samples has long attracted the interest of not only igneous petrologists but also a wide range of geoscientists. Recently, attempts have been made to use machine learning to discriminate the tectonic setting of igneous rocks. However, few studies have designed methods that are applicable to altered rocks. This study proposes a novel approach that…
- Edisi
- Vol.19, September 2023
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 10 hlm PDF, 7,603 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
A machine learning approach using legacy geophysical datasets to model Quater…
High-resolution subsurface marine mapping tools, including chirp and 3D seismic, enable the reconstruction of ancient landscapes that have been buried and subsequently submerged by marine transgression. However, the established methods for paleotopographic reconstruction require time consuming field and data interpretation efforts. Here we present a novel methodology using machine learning to e…
- Edisi
- Vol.19, September 2023
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 10 hlm PDF, 11.978 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
3D hydrostratigraphic and hydraulic conductivity modelling using supervised m…
Accurately modeling highly heterogenous aquifers is one of the big challenges in hydrogeology. There is a pressing need to develop new methods that transform high-resolution data into hydrogeological parameters representative of such aquifers. We use random forest-based machine learning to predict the distribution of hydrostratigraphic units and hydraulic conductivity (K) at a regional scale. W…
- Edisi
- Vol.19, September 2023
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 16 hlm PDF, 19.213 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Rock type classification based on petrophysical, geochemical, and core imagin…
Rock type classification is one of the most crucial steps of geological and geotechnical core logging. In conventional core logging, rock type classification is subjective and time-consuming. This study aims to automate rock type classification using Machine Learning (ML). About 35 m of core samples from five different rock types obtained from an open pit mine were logged using a Multi-Sensor C…
- Edisi
- Vol.16, December 2022
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 13 hlm PDF, 10.764 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
Machine learning – An approach for consistent rock glacier mapping and inve…
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
Forecast of convective events via hybrid model: WRF and machine learning algo…
This presents a novel hybrid 24-h forecasting model of convective weather events based on numerical simulation and machine learning algorithms. To characterize the convective events, 13-year from 2008 up to 2020 of precipitation data from the main airport stations in Rio de Janeiro, Brazil, and atmospheric discharges from the surrounding area of around 150 km are investigated. The Weather Resea…
- Edisi
- Vol.16, December 2022
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 14 hlm PDF, 14.531 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
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