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Jul 2026
Predictive Modelling and Optimization of Slope Stability Using Numerical Simulations and Machine Learning Techniques
The current study combines numerical modelling and machine learning to identify the stability of applications in nail reinforced slope study. PLAXIS LE was used to develop different slopes having different soil properties including various values for cohesion (5, 10, 15 kPa), angle of internal friction (20°, 25°, 30°),...
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· AIUB Journal of Science and... · 0 citations
Open access
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Assessing the Reliability of Empirical Correlations for Compression Index Prediction in Fine-Grained Soils
Settlement can cause significant damage to buildings and infrastructure constructed on highly compressible soils. The compression index (Cc) is a key parameter in estimating the magnitude of potential settlement. Empirical equations are commonly used to efficiently obtain Cc values, providing a practical alternative to...
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· Bentang : Jurnal Teoritis da... · 0 citations
Open access
Aug 2026
Sensitivity-Driven Evolutionary Polynomial Regression for Tropical Subgrade Permanent Deformation
This study developed an interpretable Evolutionary Polynomial Regression framework to predict permanent deformation of tropical soil subgrades in semi-rigid pavement structures. The database combined repeated-load triaxial test parameters reported in Brazilian studies with controlled mechanistic-empirical simulations r...
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Open access
Aug 2026
Geotechnical Evaluation of Gradient-Based Neural Networks for Factor of Safety Prediction in Homogeneous Soil Slopes Under Hydraulic Variability
Slope stability assessment remains a fundamental challenge in geotechnical engineering because of the complex nonlinear interactions among soil properties, slope geometry, and hydraulic conditions, particularly variations in pore-water pressure. This study investigates the reliability of Artificial Neural Network–Multi...
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Open access
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TabPFN-Based Prediction of Concrete Compressive Strength
The use of supplementary cementitious materials such as fly ash can reduce environmental impacts and improve the sustainability of concrete construction. However, the nonlinear interactions among mixture design parameters make accurate prediction of concrete compressive strength challenging. In this study, TabPFN, a pr...
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Statistical and Sensitivity Evaluation of Advanced Computational Models for Predicting Rock Mechanical Properties
The proposed framework provides accurate, robust and interpretable prediction of rock mechanical properties, demonstrating its potential for geotechnical characterization and transportation infrastructure applications.
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