Application of Bayesian Regularization Artificial Neural Network in explosion risk analysis of fixed offshore platform J Shi, Y Zhu, F Khan, G Chen Journal of loss prevention in the process industries 57, 131-141, 2019 | 98 | 2019 |
Real-time leak detection using an infrared camera and Faster R-CNN technique J Shi, Y Chang, C Xu, F Khan, G Chen, C Li Computers & Chemical Engineering 135, 106780, 2020 | 97 | 2020 |
Real-time natural gas release forecasting by using physics-guided deep learning probability model J Shi, W Xie, X Huang, F Xiao, AS Usmani, F Khan, X Yin, G Chen Journal of Cleaner Production 368, 133201, 2022 | 69 | 2022 |
A Bayesian Network model for risk analysis of deepwater drilling riser fracture failure Y Chang, C Zhang, X Wu, J Shi, G Chen, J Ye, L Xu, A Xue Ocean Engineering 181, 1-12, 2019 | 68 | 2019 |
Dynamic Bayesian network based approach for risk analysis of hydrogen generation unit leakage Y Chang, C Zhang, J Shi, J Li, S Zhang, G Chen International Journal of Hydrogen Energy 44 (48), 26665-26678, 2019 | 67 | 2019 |
Robust data-driven model to study dispersion of vapor cloud in offshore facility J Shi, F Khan, Y Zhu, J Li, G Chen Ocean Engineering 161, 98-110, 2018 | 61 | 2018 |
Methodological improvements in the risk analysis of an urban hydrogen fueling station J Shi, Y Chang, F Khan, Y Zhu, G Chen Journal of Cleaner Production 257, 120545, 2020 | 52 | 2020 |
STAMP-based analysis of deepwater well control safety X Meng, G Chen, J Shi, G Zhu, Y Zhu Journal of loss prevention in the process industries 55, 41-52, 2018 | 51 | 2018 |
Real-time pipeline leak detection and localization using an attention-based LSTM approach X Zhang, J Shi, M Yang, X Huang, AS Usmani, G Chen, J Fu, J Huang, ... Process Safety and Environmental Protection 174, 460-472, 2023 | 50 | 2023 |
Probabilistic real-time deep-water natural gas hydrate dispersion modeling by using a novel hybrid deep learning approach J Shi, J Li, AS Usmani, Y Zhu, G Chen, D Yang Energy 219, 119572, 2021 | 47 | 2021 |
Stochastic explosion risk analysis of hydrogen production facilities J Shi, B Chang, F Khan, Y Chang, Y Zhu, G Chen, C Zhang International Journal of Hydrogen Energy 45 (24), 13535-13550, 2020 | 44 | 2020 |
A multi-level early warning strategy for the LiFePO4 battery thermal runaway induced by overcharge Y Zhang, S Li, B Mao, J Shi, X Zhang, L Zhou Applied Energy 347, 121375, 2023 | 36 | 2023 |
Experimental and numerical study of gas explosion from semi-submersible platform J Shi, H Zhang, X Huang, J Wen, G Chen, G Chen, A Yu Ocean Engineering 295, 116958, 2024 | 32 | 2024 |
Artificial bee colony Based Bayesian Regularization Artificial Neural Network approach to model transient flammable cloud dispersion in congested area J Shi, X Li, F Khan, Y Chang, Y Zhu, G Chen Process Safety and Environmental Protection 128, 121-127, 2019 | 32 | 2019 |
A simplified statistic-based procedure for gas dispersion prediction of fixed offshore platform J Shi, J Li, Y Zhu, H Hao, G Chen, B Xie Process Safety and Environmental Protection 114, 48-63, 2018 | 32 | 2018 |
Stochastic analysis of explosion risk for ultra-deep-water semi-submersible offshore platforms J Shi, Y Zhu, D Kong, F Khan, J Li, G Chen Ocean Engineering 172, 844-856, 2019 | 31 | 2019 |
Hydrogen leakage location prediction at hydrogen refueling stations based on deep learning Y Bi, Q Wu, S Wang, J Shi, H Cong, L Ye, W Gao, M Bi Energy 284, 129361, 2023 | 30 | 2023 |
Towards deep probabilistic graph neural network for natural gas leak detection and localization without labeled anomaly data X Zhang, J Shi, X Huang, F Xiao, M Yang, J Huang, X Yin, AS Usmani, ... Expert Systems with Applications 231, 120542, 2023 | 30 | 2023 |
Real-time natural gas explosion modeling of offshore platforms by using deep learning probability approach J Shi, H Zhang, J Li, W Xie, W Zhao, AS Usmani, G Chen Ocean Engineering 276, 114244, 2023 | 29 | 2023 |
AIoT-enabled digital twin system for smart tunnel fire safety management X Zhang, Y Jiang, X Wu, Z Nan, Y Jiang, J Shi, Y Zhang, X Huang, ... Developments in the Built Environment 18, 100381, 2024 | 28 | 2024 |