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Landslide susceptibility map** using automatically constructed CNN architectures with pre-slide topographic DEM of deep-seated catastrophic landslides caused by Typhoon Talas
There has been an increasing demand for detailed and accurate landslide maps and inventories in disaster-prone areas of subtropical and temperate...
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The high-resolution community velocity model V2.0 of southwest China, constructed by joint body and surface wave tomography of data recorded at temporary dense arrays
The Sichuan-Yunnan area is located at the southeastern margin of the Tibetan Plateau, where tectonic movement is strong with deep and large faults...
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Infrasound Event Classification Fusion Model Based on Multiscale SE-CNN and BiLSTM
The classification of infrasound events has considerable importance in improving the capability to identify the types of natural disasters. The...
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Local dynamic update methods for 3D geological body structure model and voxel model
Due to the complexity of geological structures, the uncertainty of geological phenomena, the massive amount of geological data, and the diversity of...
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Constraint information extraction for 3D geological modelling using a span-based joint entity and relation extraction model
Data sparsity has long been a problem in 3D geological modeling work. The geometric, topological, and attribute information of geological bodies in...
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Development of a building information model-guided post-earthquake building inspection framework using 3D synthetic environments
Computer vision-based inspection methods show promise for automating post-earthquake building inspections. These methods survey a building with...
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Extraction of temporal information from social media messages using the BERT model
Temporal information extraction from social media messages is of critical importance to several geographical applications. Combined with the...
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An automatic model selection-based machine learning approach to predict seawater intrusion into coastal aquifers
Concerns about seawater intrusion resulting from unplanned mining of groundwater from coastal aquifers have become a global issue. To address this,...
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Optimization of the Low-Impact Development Facility Area Based on a Surrogate Model
Low-impact development (LID) facilities constitute an important element of sponge cities. In this paper, a system of siting suitability indicators...
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Automatic, Point-Wise Rock Image Enhancement by Novel Unsupervised Deep Learning: Dataset Establishment and Model Development
Rock images play a vital role in providing data for engineering geological studies. However, low-light (a.k.a. dark) rock images are often obtained,...
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Landslide susceptibility prediction and map** using the LD-BiLSTM model in seismically active mountainous regions
Machine learning models have been widely used in landslide susceptibility prediction. However, landslide multidimensional feature extraction, model...
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Machine learning of three-dimensional subsurface geological model for a reclamation site in Hong Kong
Land reclamation from ocean is a major solution to deal with land shortage in coastal megacities such as Hong Kong. The primary geotechnical risk...
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A Framework on Fast Map** of Urban Flood Based on a Multi-Objective Random Forest Model
Fast and accurate prediction of urban flood is of considerable practical importance to mitigate the effects of frequent flood disasters in advance....
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Oil Spill Identification based on Dual Attention UNet Model Using Synthetic Aperture Radar Images
Oil spills cause tremendous damage to marine, coastal environments, and ecosystems. Previous deep learning-based studies have addressed the task of...
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Research on Elaborate Construction of Complex 3D Geological Model and In-Situ Stress Inversion
In order to obtain the distribution characteristics of the regional stress field in deep coal-bearing strata, a method for constructing a complex...
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An improved LSSVM discrimination model based on factor analysis and moth flame optimization algorithm for identifying water inrush sources across multiple aquifers in mines
To accurately and swiftly identifying the source of water inrush in mines, a discrimination model based on factor analysis (FA) and the moth flame...
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Robust Multi-Output Machine Learning Regression for Seismic Hazard Model Using Peak Crust Acceleration Case Study, Turkey, Iraq and Iran
This paper for the first time improved a Robust Multi-Output machine learning regression model for seismic hazard zoning of Turkey, Iraq and Iran...
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What is this article about? Generative summarization with the BERT model in the geosciences domain
In recent years, a large amount of data has been accumulated, such as those recorded in geological journals and report literature, which contain a...
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A regional early warning model of geological hazards based on big data of real-time rainfall
The warning accuracy, false alarm rate and timeliness of regional geological hazard early warning models (GHEWMs) have an important impact on...
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Optimization of Well Location in W Reservoir Based on Machine Learning Agent Model
As the blood of industry, petroleum is very important to the development of national economy and National Energy Security. In the process of oilfield...