专题：Geotechnical Engineering and Analysis

This cluster of papers focuses on geotechnical engineering, particularly on factors of safety and reliability. It covers topics such as slope stability analysis, spatial variability of soil properties, probabilistic methods for stability analysis, tunneling effects, and ground movements due to excavation. The papers also delve into finite element analysis, Bayesian optimization for predicting soil properties, and the impact of tunneling on existing infrastructure.
最新文献
Intelligent control and optimization of shield tunneling machines in tunnel construction: Insights from excavation parameter data analysis and interpretable machine learning

article Full Text OpenAlex

Nonlinear progressive failure mechanism and shear strength model of deeply buried jinping marble under direct shear

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Reliability analysis of pile bearing capacity using state-of-the-art hybrid Neuro-Fuzzy ML approaches

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Spatiotemporal-information-driven surrogate modeling for predictive analysis of shield tunneling-induced settlement

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Tunnel Collapse Risk Analysis Based on Attribute Mathematical Theory and TSP Geological Forecast Technique

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Behaviour of Single Tapered Belled and Straight Bored Piles Under Inclined Load: A Comparative Study Using PLAXIS 3D

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Third Workshop on the Future of Machine Learning in Geotechnics (3FOMLIG), 15-17 October 2025, Florence, Italy

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Grouting optimization for tunnel water-inrush disaster mitigation in jointed rock masses using discrete fracture network modeling

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Deterministic versus random finite element analysis of tunnel response: a case study in munich area

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A metaheuristic-based ANN framework for overbreak prediction in the Rishikesh-Karnaprayag railway tunnel

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近5年高被引文献
Materials Today: Proceedings

article Full Text OpenAlex 1386 FWCI0

Geotechnical Testing Journal

paratext Full Text OpenAlex 345 FWCI0

Application of artificial intelligence in geotechnical engineering: A state-of-the-art review

review Full Text OpenAlex 310 FWCI43.4096

Predictive Performances of Ensemble Machine Learning Algorithms in Landslide Susceptibility Mapping Using Random Forest, Extreme Gradient Boosting (XGBoost) and Natural Gradient Boosting (NGBoost)

article Full Text OpenAlex 307 FWCI83.6908

Slope stability prediction using ensemble learning techniques: A case study in Yunyang County, Chongqing, China

article Full Text OpenAlex 233 FWCI65.523

Centrifuge modelling of landslides and landslide hazard mitigation: A review

review Full Text OpenAlex 229 FWCI65.8209

Future of machine learning in geotechnics

article Full Text OpenAlex 223 FWCI33.4298

Prediction of Pile Bearing Capacity Using XGBoost Algorithm: Modeling and Performance Evaluation

article Full Text OpenAlex 201 FWCI22.3266

Regional rainfall-induced landslide hazard warning based on landslide susceptibility mapping and a critical rainfall threshold

article Full Text OpenAlex 198 FWCI54.8031

Landslide susceptibility prediction using slope unit-based machine learning models considering the heterogeneity of conditioning factors

article Full Text OpenAlex 181 FWCI49.4401