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Applied Sciences, Vol. 16, Pages 9094: 3D Geological Modeling Using Geostatistical, Deterministic, and Artificial Intelligence Algorithms: A Comparative Analysis for Delineating Mineralized Zones
15+ hour, 21+ min ago (347+ words) The delineation of mineralized zones within deposits is inherently associated with geological uncertainty, directly impacting resource-reserve estimation and eventual extraction. This study presents a comparative analysis of three geological modeling techniques, including Indicator Kriging (IK), Nearest Neighbor (NN), and Multilayer…...
Applied Sciences, Vol. 16, Pages 8920: Machine Learning Based on Hybrid Optimization Algorithm for the Prediction and Risk Assessment of Rock Tunnel Lining Displacement
5+ day, 16+ hour ago (433+ words) Accurate prediction of tunnel vault displacement and reliable assessment of deformation risk are essential for tunnel safety management under complex geological conditions. This study develops an integrated data-driven framework combining machine-learning prediction, metaheuristic hyperparameter optimization, statistical model comparison, and uncertainty-informed…...
Applied Sciences, Vol. 16, Pages 8845: Characterization of Geothermal Reservoir Structures Based on a Deep Generative Neural Network with Local Edge Pattern Learning
1+ week, 1+ day ago (420+ words) Accurate three-dimensional (3D) characterization of geothermal reservoirs is crucial for resource assessment and development, yet it remains a significant challenge due to sparse direct observations and the complex, heterogeneous nature of subsurface geology. While deep learning has emerged as a powerful…...
Applied Sciences, Vol. 16, Pages 8812: Optimised Machine Learning for MASW-Based Zonation of Weak Alluvial Soils Using Anchor-Based SPT/SCPT Calibration
1+ week, 2+ day ago (433+ words) Weak alluvial soils are difficult to delineate where penetration-test data are sparse and stiffness varies rapidly with depth. This study presents a novel goal-attainment-optimised machine learning framework that combines multichannel analysis of surface waves (MASW) with anchor-based standard penetration test…...
Applied Sciences, Vol. 16, Pages 8773: Mechanism-Based Insights and Ablation Study of Multi-Constraint Strategies for Physics-Informed Neural Networks in Shock-Dominated Dam-Break Flows
1+ week, 3+ day ago (558+ words) Physics-informed neural networks (PINNs) provide mesh-free approximation and rapid inference for dam-break flood simulations. However, the effectiveness and underlying mechanisms of different enhancement strategies for engineering-representative shock-dominated flows remain insufficiently understood. To address this issue, this study established a controlled…...
Applied Sciences, Vol. 16, Pages 8652: Basin-Wide Monitoring and PIM Parameter Inversion of Mining Subsidence Using UAV-LiDAR
1+ week, 6+ day ago (473+ words) Accurate, comprehensive, and spatially continuous monitoring of mining-induced surface subsidence is essential for geohazard prevention, ecological restoration, and safe mining. Conventional approaches, however, are limited by the sparse spatial distribution of GNSS observations, the difficulty of InSAR in resolving large…...
Applied Sciences, Vol. 16, Pages 8612: An Effective Method for Digital Rock Reconstruction with Enhanced Pore Connectivity
2+ week, 1+ day ago (467+ words) Digital rock technology is essential for characterizing the petrophysical properties of tight reservoirs. However, conventional construction methods often yield models with insufficient pore connectivity due to low porosity and complex nanopore structures. To address this limitation, we propose a novel…...
Applied Sciences, Vol. 16, Pages 8401: Semi-Supervised Acoustic Impedance Inversion Based on a Hybrid Deep Learning Network
3+ week, 47+ min ago (487+ words) Accurate estimation of subsurface acoustic impedance is fundamental to quantitative reservoir characterization in seismic exploration. Nevertheless, a single network architecture cannot adequately represent both the local details and the global trends of seismic records within a unified framework, while the…...
Applied Sciences, Vol. 16, Pages 8360: Optimizing Machine Learning Models for Predicting Rock Cohesion and Angle of Internal Friction: A Comparative Study of Lithological Analysis, Robustness Assessment, and SHAP Explanations
3+ week, 1+ day ago (501+ words) Rock cohesion (c) and angle of internal friction (φ) are core parameters for rock mass stability analysis and engineering design; however, traditional triaxial tests are costly and time-consuming, limiting their availability in preliminary engineering assessments. To address this limitation, this study…...
Applied Sciences, Vol. 16, Pages 8332: Enhancing End-to-End Graphite Ore Grade Detection via Boundary-Aware Refinement, Bidirectional Fusion, and Difficulty-Aware Distillation
3+ week, 2+ day ago (453+ words) Graphite ore grade sorting is a key step toward intelligent mineral processing; however, it faces three representational contradictions: ambiguous classification posteriors at grade boundaries, asymmetric multi-scale feature interaction, and the mismatch between class-agnostic self-distillation assignment and sample-level difficulty. Targeting these,…...