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Pin ZHANG (张品)
Pin ZHANG (张品)
Royal Society-Newton International Fellow, University of Cambridge
在 cam.ac.uk 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Prediction of maximum surface settlement caused by earth pressure balance (EPB) shield tunneling with ANN methods
RP Chen, P Zhang, X Kang, ZQ Zhong, Y Liu, HN Wu
Soils and Foundations 59 (2), 284-295, 2019
1952019
Hybrid meta-heuristic and machine learning algorithms for tunneling-induced settlement prediction: A comparative study
P Zhang, HN Wu, RP Chen, THT Chan
Tunnelling and Underground Space Technology 99, 103383, 2020
1612020
Real-time analysis and regulation of EPB shield steering using Random Forest
P Zhang, RP Chen, HN Wu
Automation in Construction 106, 102860, 2019
1572019
Prediction of shield tunneling-induced ground settlement using machine learning techniques
R Chen, P Zhang, H Wu, Z Wang, Z Zhong
Frontiers of Structural and Civil Engineering 13 (6), 1363-1378, 2019
1432019
A novel hybrid surrogate intelligent model for creep index prediction based on particle swarm optimization and random forest
P Zhang, ZY Yin, YF Jin, THT Chan
Engineering Geology 265, 105328, 2020
1412020
Deformation and stress characteristics of existing twin tunnels induced by close-distance EPBS under-crossing
RP Chen, XT Lin, X Kang, ZQ Zhong, Y Liu, P Zhang, HN Wu
Tunnelling and Underground Space Technology 82, 468-481, 2018
1192018
A novel feature selection method based on global sensitivity analysis with application in machine learning-based prediction model
P Zhang
Applied Soft Computing 85, 105859, 2019
1012019
Intelligent modelling of clay compressibility using hybrid meta-heuristic and machine learning algorithms
P Zhang, ZY Yin, YF Jin, THT Chan, FP Gao
Geoscience Frontiers 12 (1), 441-452, 2021
952021
A critical evaluation of machine learning and deep learning in shield-ground interaction prediction
P Zhang, HN Wu, RP Chen, T Dai, FY Meng, HB Wang
Tunnelling and Underground Space Technology 106, 103593, 2020
912020
State-of-the-art review of machine learning applications in constitutive modeling of soils
P Zhang, ZY Yin, YF Jin
Archives of Computational Methods in Engineering 28 (5), 3661-3686, 2021
822021
An AI‐based model for describing cyclic characteristics of granular materials
P Zhang, ZY Yin, YF Jin, GL Ye
International Journal for Numerical and Analytical Methods in Geomechanics …, 2020
772020
Bayesian neural network-based uncertainty modelling: application to soil compressibility and undrained shear strength prediction
P Zhang, ZY Yin, YF Jin
Canadian Geotechnical Journal 59 (4), 546-557, 2022
632022
A novel deep learning-based modelling strategy from image of particles to mechanical properties for granular materials with CNN and BiLSTM
P Zhang, ZY Yin
Computer Methods in Applied Mechanics and Engineering 382, 113858, 2021
612021
Reinforcement learning based optimizer for improvement of predicting tunneling-induced ground responses
P Zhang, H Li, QP Ha, ZY Yin, RP Chen
Advanced Engineering Informatics 45, 101097, 2020
572020
Success and challenges in predicting TBM penetration rate using recurrent neural networks
F Shan, X He, DJ Armaghani, P Zhang, D Sheng
Tunnelling and Underground Space Technology 130, 104728, 2022
552022
Physics-Informed Multifidelity Residual Neural Networks for Hydromechanical Modeling of Granular Soils and Foundation Considering Internal Erosion
P Zhang, ZY Yin, YF Jin, J Yang, B Sheil
Journal of Engineering Mechanics 148 (4), 04022015, 2022
472022
Machine Learning-Based Modelling of Soil Properties for Geotechnical Design: Review, Tool Development and Comparison
P Zhang, ZY Yin, YF Jin
Archives of Computational Methods in Engineering 29, 1229-1245, 2022
442022
An AIoT-based system for real-time monitoring of tunnel construction
P Zhang, RP Chen, T Dai, ZT Wang, K Wu
Tunnelling and Underground Space Technology 109, 103766, 2021
422021
Ground settlement induced by tunneling crossing interface of water-bearing mixed ground: A lesson from Changsha, China
P Zhang, RP Chen, HN Wu, Y Liu
Tunnelling and Underground Space Technology 96, 103224, 2020
422020
Modelling the mechanical behaviour of soils using machine learning algorithms with explicit formulations
P Zhang, ZY Yin, YF Jin, XF Liu
Acta Geotechnica 17 (4), 1403-1422, 2022
412022
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