| 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 | 73 | 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 | 70 | 2020 |
| 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 | 58 | 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 | 50 | 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 | 50 | 2018 |
| 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 | 47 | 2022 |
| 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 | 45 | 2018 |
| 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 | 38 | 2021 |
| 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 | 36 | 2020 |
| 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 | 31 | 2020 |
| 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 | 28 | 2018 |
| 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 | 27 | 2019 |
| 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 | 25 | 2019 |
| Effect of gas composition on dispersion characteristics of blowout gas on offshore platform D Yang, G Chen, J Shi, X Li International Journal of Naval Architecture and Ocean Engineering 11 (2 …, 2019 | 24 | 2019 |
| A novel approach for hazardous area identification of toxic gas leakage accidents on offshore facilities D Yang, G Chen, J Shi, Y Zhu, Z Dai Ocean Engineering 217, 107926, 2020 | 21 | 2020 |
| 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 | 17 | 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 | 16 | 2023 |
| Assessment on blast loading resistance capacity of corrugations on offshore cabins based on the P–I model J Shi, Y Zhu, G Chen, R Zhang, Z Guo Process Safety and Environmental Protection 105, 237-249, 2017 | 13 | 2017 |
| Real-time plume tracking using transfer learning approach J Shi, W Xie, J Li, X Zhang, X Huang, AS Usmani, F Khan, G Chen Computers & Chemical Engineering 172, 108172, 2023 | 11 | 2023 |
| Underwater gas leak detection using an autonomous underwater vehicle (robotic fish) S Hu, A Feng, J Shi, J Li, F Khan, H Zhu, J Chen, G Chen Process Safety and Environmental Protection 167, 89-96, 2022 | 11 | 2022 |
