| Cemented paste backfill for mineral tailings management: Review and future perspectives C Qi, A Fourie Minerals Engineering 144, 106025, 2019 | 548 | 2019 |
| Recycling phosphogypsum and construction demolition waste for cemented paste backfill and its environmental impact Q Chen, Q Zhang, C Qi, A Fourie, C Xiao Journal of Cleaner Production 186, 418-429, 2018 | 360 | 2018 |
| A spatially explicit deep learning neural network model for the prediction of landslide susceptibility D Van Dao, A Jaafari, M Bayat, D Mafi-Gholami, C Qi, H Moayedi, ... Catena 188, 104451, 2020 | 307 | 2020 |
| Neural network and particle swarm optimization for predicting the unconfined compressive strength of cemented paste backfill C Qi, A Fourie, Q Chen Construction and Building Materials 159, 473-478, 2018 | 268 | 2018 |
| Slope stability prediction using integrated metaheuristic and machine learning approaches: A comparative study C Qi, X Tang Computers & Industrial Engineering 118, 112-122, 2018 | 231 | 2018 |
| Big data management in the mining industry C Qi International Journal of Minerals, Metallurgy and Materials 27 (2), 131-139, 2020 | 226 | 2020 |
| A strength prediction model using artificial intelligence for recycling waste tailings as cemented paste backfill C Qi, A Fourie, Q Chen, Q Zhang Journal of Cleaner Production 183, 566-578, 2018 | 222 | 2018 |
| Experimental investigation on the relationship between pore characteristics and unconfined compressive strength of cemented paste backfill L Liu, Z Fang, C Qi, B Zhang, L Guo, KIIL Song Construction and Building Materials 179, 254-264, 2018 | 205 | 2018 |
| A new procedure for recycling waste tailings as cemented paste backfill to underground stopes and open pits H Lu, C Qi, Q Chen, D Gan, Z Xue, Y Hu Journal of Cleaner Production 188, 601-612, 2018 | 184 | 2018 |
| Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping BT Pham, T Nguyen-Thoi, C Qi, T Van Phong, J Dou, LS Ho, H Van Le, ... Catena 195, 104805, 2020 | 142 | 2020 |
| An intelligent modelling framework for mechanical properties of cemented paste backfill C Qi, Q Chen, A Fourie, Q Zhang Minerals Engineering 123, 16-27, 2018 | 141 | 2018 |
| Permeability prediction of porous media using a combination of computational fluid dynamics and hybrid machine learning methods J Tian, C Qi, Y Sun, ZM Yaseen, BT Pham Engineering with Computers 37, 3455-3471, 2021 | 138 | 2021 |
| Experimental investigation on the strength characteristics of cement paste backfill in a similar stope model and its mechanism Q Chen, Q Zhang, A Fourie, X Chen, C Qi Construction and Building Materials 154, 34-43, 2017 | 137 | 2017 |
| Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: A case study in Iraq K Khosravi, P Daggupati, MT Alami, SM Awadh, MI Ghareb, M Panahi, ... Computers and Electronics in Agriculture 167, 105041, 2019 | 130 | 2019 |
| An experimental study on the early-age hydration kinetics of cemented paste backfill L Liu, P Yang, C Qi, B Zhang, L Guo, KIIL Song Construction and Building Materials 212, 283-294, 2019 | 128 | 2019 |
| A comparative study of kernel logistic regression, radial basis function classifier, multinomial naïve bayes, and logistic model tree for flash flood susceptibility mapping BT Pham, TV Phong, HD Nguyen, C Qi, N Al-Ansari, A Amini, LS Ho, ... Water 12 (1), 239, 2020 | 125 | 2020 |
| Lithium slag and fly ash-based binder for cemented fine tailings backfill Y He, Q Chen, C Qi, Q Zhang, C Xiao Journal of Environmental Management 248, 109282, 2019 | 122 | 2019 |
| A novel hybrid soft computing model using random forest and particle swarm optimization for estimation of undrained shear strength of soil BT Pham, C Qi, LS Ho, T Nguyen-Thoi, N Al-Ansari, MD Nguyen, ... Sustainability 12 (6), 2218, 2020 | 121 | 2020 |
| Numerical study on the pipe flow characteristics of the cemented paste backfill slurry considering hydration effects L Liu, Z Fang, C Qi, B Zhang, L Guo, KIIL Song Powder technology 343, 454-464, 2019 | 113 | 2019 |
| Prediction of evaporation in arid and semi-arid regions: A comparative study using different machine learning models ZM Yaseen, AM Al-Juboori, U Beyaztas, N Al-Ansari, KW Chau, C Qi, ... Engineering applications of computational fluid mechanics 14 (1), 70-89, 2020 | 108 | 2020 |
Qiusong ChenCentral South UniversityAdresse e-mail validée de csu.edu.cn
