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°),...
The potential effectiveness of the proposed robustness-oriented evaluation framework for ML-assisted Ra prediction under limited-data machining conditions is supported, and ELM achieved the highest prediction accuracy.
Phong Thanh Huynh, Tien V. T. Nguyen, Huynh Thanh Thuong· Engineering Research Express· 0 citations
A prediction method based on particle swarm optimisation (PSO) and a one-dimensional convolutional neural network (1D-CNN) was developed and integrated into an online system that enables single tube wall thickness prediction, sawing parameter calculation, and batch visualisation for process adjustment and sawing decisi...
Yue Yu, Xiao-chen Wang, Jin-bo Zhou et al.· Ironmaking & Steelmaking...· 0 citations
The proposed framework combined a curated database, neural network-based curve prediction, and hyperparameter optimization, providing a robust approach for evaluating the soil arching effect, providing a robust approach for evaluating the soil arching effect.
Cheng-shuang Yin, Liu-mei Wei, Han-lin Wang et al.· Transportation Infrastructur...· 0 citations
This study applies several machine learning models to predict the Marshall stability of Stone Mastic Asphalt mixtures incorporating steel slag as a partial replacement for conventional coarse aggregates, with CatBoost providing the best performance.
T. Nguyen, Hoang-Long Nguyen, N. Trần et al.· Journal of Science and Trans...· 0 citations
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