Xuan Zhong, Peng Ni, Kai Xu, Xulong Cai, Minghe Yang, “Wellbore risk levels prediction based on BO-CatBoost model and rough set theory”, Meas. Sci. Technol., 36:8 (2025), 086011
Bingran Yang, Xuedong Jing, “Spatial Error Prediction and Compensation of Industrial Robots Based on Extended Joints and BO-XGBoost”, Sensors, 25:20 (2025), 6422
Xuefeng An, Fei Zheng, Yuyong Jiao, Zhi Li, You Zhang, Lingling He, “Optimized machine learning models for predicting crown convergence of plateau mountain tunnels”, Transportation Geotechnics, 46 (2024), 101254
Xuefeng An, Hanbin Luo, Fei Zheng, Yuyong Jiao, Jianfeng Qi, You Zhang, “Explainable deep learning-based dynamic prediction of surface settlement considering temporal characteristics during deep excavation”, Applied Soft Computing, 167 (2024), 112273
Chen Wang, Qiuyue Wu, Jiaxin Liang, Fayun Liang, Xiong (Bill) Yu, “Establishment and implementation of an artificial intelligent flume for investigating local scour around underwater foundations”, Transportation Geotechnics, 2024, 101433
Jinwoo Im, Felipe P. J. de Barros, Sami F. Masri, “Data-driven identification of partial differential equations for multi-physics systems using stochastic optimization”, Nonlinear Dyn, 111:3 (2023), 1987
Guarino A., Trinchero R., Canavero F., Spagnuolo G., “A Fast Fuel Cell Parametric Identification Approach Based on Machine Learning Inverse Models”, Energy, 239:C (2022), 122140
Hai-ying Fu, Yan-yan Zhao, Hao-jiang Ding, Yun-kang Rao, Tao Yang, Ming-zhe Zhou, “A novel intelligent displacement prediction model of karst tunnels”, Sci Rep, 12:1 (2022)
Junlong Sun, Shunchuan Wu, Huajin Zhang, Xiaoqiang Zhang, Tao Wang, “Based on multi-algorithm hybrid method to predict the slope safety factor– stacking ensemble learning with bayesian optimization”, Journal of Computational Science, 59 (2022), 101587
Konstantin Rybakov, N.S. Severina, M. Mikilyan, “Spectral representation of stochastic integration operators”, MATEC Web of Conferences, 362 (2022), 01027