Ditapis dengan
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
Complex Study of Settlements Dating from the Paleolithic to Medieval Period i…
Soil, geochemical, microbiological, and archeological studies were conducted at eight settlements dating from the Paleolithic to Late Medieval and Modern Ages near the southern Trans-Urals Mountains, Russia. The forest-steppe landscapes, rivers, and abundant mineral resources have attracted people to the region since ancient times. Cultural layers (CLs) are marked by finds of ceramics fragments…
- Edisi
- Vol.15, Issue 1, January 2025
- ISBN/ISSN
- 2076-3263
- Deskripsi Fisik
- 28 hlm PDF, 5.769 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
Assessing the ecological vulnerability of forest landscape to agricultural fr…
Forest conservation in human-dominated tropical landscapes ensures provision of major ecosystem services. However, conservation goals are threatened by growing demands for agricultural products. As the expansion of agricultural frontiers continues to exert increasing pressure on forest cover, it is crucial to provide indicators on forest vulnerability to improve our understanding of forest dyna…
- Edisi
- Vol.84, February 2020
- ISBN/ISSN
- 1569-8432
- Deskripsi Fisik
- 13 hlm PDF, 13.168 KB
- Judul Seri
- International Journal of Applied Earth Observation and Geoinformation - Open Access
- No. Panggil
- 910.285
Research on the prediction method for fluvial-phase sandbody connectivity bas…
The connectivity of sandbodies is a key constraint to the exploration effectiveness of Bohai A Oilfield. Conventional connectivity studies often use methods such as seismic attribute fusion, while the development of contiguous composite sandbodies in this area makes it challenging to characterize connectivity changes with conventional seismic attributes. Aiming at the above problem in the Bohai…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 8 hlm PDF, 6.809 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Benchmarking data handling strategies for landslide susceptibility modeling u…
Machine learning (ML) algorithms are frequently used in landslide susceptibility modeling. Different data handling strategies may generate variations in landslide susceptibility modeling, even when using the same ML algorithm. This research aims to compare the combinations of inventory data handling, cross validation (CV), and hyperparameter tuning strategies to generate landslide susceptibilit…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 16 hlm PDF, 33.426 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Integrating the artificial intelligence and hybrid machine learning algorithm…
The aim of the current work is to compare susceptibility maps of landslides produced using machine learning techniques i.e. multilayer perception neural nets (MLP), kernel logistic regression (KLR), random forest (RF), and multivariate adaptive regression splines (MARS); novel ensemble approaches i.e. MLP-Bagging, KLR-Bagging, RF-Bagging and MARS-Bagging in the Kurseong-Himalayan region. For th…
- Edisi
- Vol.3, December 2022
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 14 hlm PDF, 5.975 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
A study on geological structure prediction based on random forest method
The Xingmeng orogenic belt is located in the eastern section of the Central Asian orogenic belt, which is one of the key areas to study the formation and evolution of the Central Asian orogenic belt. At present, there is a huge controversy over the closure time of the Paleo-Asian Ocean in the Xingmeng orogenic belt. One of the reasons is that the genetic tectonic setting of the Carboniferous vo…
- Edisi
- Vol.3, December 2022
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 11 hlm PDF, 7.913 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Rapid identification of high-quality marine shale gas reservoirs based on the…
The identification of high-quality marine shale gas reservoirs has always been a key task in the exploration and development stage. However, due to the serious nonlinear relationship between the logging curve response and high-quality reservoirs, the rapid identification of high-quality reservoirs has always been a problem of low accuracy. This study proposes a combination of the oversampling m…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 6 hlm PDF, 1.091 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Data-driven approaches for time series prediction of daily production in the …
The Sulige tight gas field is presently the largest gas field in China. Owing to the ultralow permeability and strong heterogeneity of the reservoirs in Sulige, the number of production wells has exceeded 3,000, keeping the stable gas supply in the decade. Thus, the daily production prediction of gas wells is significant for monitoring production and for implementing and evaluating stimulation …
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 6 hlm PDF, 1.029 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
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