| Performance evaluation of hybrid WOA-XGBoost, GWO-XGBoost and BO-XGBoost models to predict blast-induced ground vibration Y Qiu, J Zhou, M Khandelwal, H Yang, P Yang, C Li Engineering with Computers 38 (Suppl 5), 4145-4162, 2022 | 334 | 2022 |
| Optimization of support vector machine through the use of metaheuristic algorithms in forecasting TBM advance rate J Zhou, Y Qiu, S Zhu, DJ Armaghani, C Li, H Nguyen, S Yagiz Engineering Applications of Artificial Intelligence 97, 104015, 2021 | 275 | 2021 |
| Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques J Zhou, Y Qiu, DJ Armaghani, W Zhang, C Li, S Zhu, R Tarinejad Geoscience Frontiers 12 (3), 101091, 2021 | 245 | 2021 |
| Random forests and cubist algorithms for predicting shear strengths of rockfill materials J Zhou, E Li, H Wei, C Li, Q Qiao, DJ Armaghani Applied sciences 9 (8), 1621, 2019 | 230 | 2019 |
| Performance evaluation of hybrid FFA-ANFIS and GA-ANFIS models to predict particle size distribution of a muck-pile after blasting J Zhou, C Li, CA Arslan, M Hasanipanah, H Bakhshandeh Amnieh Engineering with computers 37 (1), 265-274, 2021 | 139 | 2021 |
| Rockburst prediction in hard rock mines developing bagging and boosting tree-based ensemble techniques S Wang, J Zhou, C Li, DJ Armaghani, X Li, HS Mitri Journal of Central South University 28 (2), 527-542, 2021 | 106 | 2021 |
| Stability analysis of underground mine hard rock pillars via combination of finite difference methods, neural networks, and Monte Carlo simulation techniques C Li, J Zhou, DJ Armaghani, X Li Underground Space 6 (4), 379-395, 2021 | 96 | 2021 |
| Use of intelligent methods to design effective pattern parameters of mine blasting to minimize flyrock distance J Zhou, M Koopialipoor, BR Murlidhar, SA Fatemi, MM Tahir, ... Natural Resources Research 29, 625-639, 2020 | 89 | 2020 |
| Development of a new methodology for estimating the amount of PPV in surface mines based on prediction and probabilistic models (GEP-MC) J Zhou, C Li, M Koopialipoor, D Jahed Armaghani, B Thai Pham International Journal of Mining, Reclamation and Environment 35 (1), 48-68, 2021 | 76 | 2021 |
| Developing hybrid ELM-ALO, ELM-LSO and ELM-SOA models for predicting advance rate of TBM C Li, J Zhou, M Tao, K Du, S Wang, DJ Armaghani, ET Mohamad Transportation Geotechnics 36, 100819, 2022 | 62 | 2022 |
| Six novel hybrid extreme learning machine–swarm intelligence optimization (ELM–SIO) models for predicting backbreak in open-pit blasting C Li, J Zhou, M Khandelwal, X Zhang, M Monjezi, Y Qiu Natural Resources Research 31 (5), 3017-3039, 2022 | 53 | 2022 |
| Application of Six Metaheuristic Optimization Algorithms and Random Forest in the uniaxial compressive strength of rock prediction J Li, C Li, S Zhang Applied Soft Computing 131, 109729, 2022 | 47 | 2022 |
| Stochastic assessment of hard rock pillar stability based on the geological strength index system C Li, J Zhou, DJ Armaghani, W Cao, S Yagiz Geomechanics and Geophysics for Geo-Energy and Geo-Resources 7, 1-24, 2021 | 41 | 2021 |
| COSMA-RF: New intelligent model based on chaos optimized slime mould algorithm and random forest for estimating the peak cutting force of conical picks J Zhou, Y Dai, K Du, M Khandelwal, C Li, Y Qiu Transportation Geotechnics 36, 100806, 2022 | 40 | 2022 |
| Rockburst prediction and prevention in underground space excavation J Zhou, Y Zhang, C Li, H He, X Li Underground Space 14, 70-98, 2024 | 38 | 2024 |
| Stability prediction of hard rock pillar using support vector machine optimized by three metaheuristic algorithms C Li, J Zhou, K Du, D Dias International Journal of Mining Science and Technology 33 (8), 1019-1036, 2023 | 37 | 2023 |
| Development of a hybrid artificial intelligence model to predict the uniaxial compressive strength of a new aseismic layer made of rubber-sand concrete X Mei, C Li, Q Sheng, Z Cui, J Zhou, D Dias Mechanics of Advanced Materials and Structures 30 (11), 2185-2202, 2023 | 37 | 2023 |
| A kernel extreme learning machine-grey wolf optimizer (KELM-GWO) model to predict uniaxial compressive strength of rock C Li, J Zhou, D Dias, Y Gui Applied Sciences 12 (17), 8468, 2022 | 33 | 2022 |
| Machine learning models to predict the tunnel wall convergence J Zhou, Y Chen, C Li, Y Qiu, S Huang, M Tao Transportation Geotechnics 41, 101022, 2023 | 31 | 2023 |
| A new hybrid model of information entropy and unascertained measurement with different membership functions for evaluating destressability in burst-prone underground mines J Zhou, C Chen, K Du, D Jahed Armaghani, C Li Engineering with Computers, 1-19, 2020 | 28 | 2020 |
Jian ZhouProfessor, School of Resources and Safety Engineering, Central South UniversityEmail verificata su csu.edu.cn