Ditapis dengan
A comparative study on machine learning approaches for rock mass classificati…
Current rock engineering design in drill and blast tunnelling primarily relies on engineers' observational assessments. Measure While Drilling (MWD) data, a high-resolution sensor dataset collected during tunnel excavation, is underutilised, mainly serving for geological visualisation. This study aims to automate the translation of MWD data into actionable metrics for rock engineering. It seeks…
- Edisi
- Vol.24, December 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 24 hlm PDF, 15.152 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
Stochastic 3D modelling of discrete sediment bodies for geotechnical applicat…
In the course of engineering geological ground characterizations, internal structures of sediments are often simplified to continuous units and structures like lenses are drawn in cross sections based on geologists’ experience. Seeing this as oversimplifications, we propose discrete sediment body (DSB) modelling which is a computational workflow that permits generation of 3D meshes of sedimen…
- Edisi
- Vol.11, September 2021
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 11 hlm PDF, 13.051 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
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