| Early prediction of the 2019 novel coronavirus outbreak in the mainland China based on simple mathematical model L Zhong, L Mu, J Li, J Wang, Z Yin, D Liu IEEE access 8, 51761-51769, 2020 | 244 | 2020 |
| Streamflow prediction using deep learning neural network: case study of Yangtze River D Liu, W Jiang, L Mu, S Wang IEEE access 8, 90069-90086, 2020 | 108 | 2020 |
| Prediction of Yangtze River streamflow based on deep learning neural network with El Niño–Southern Oscillation S Ha, D Liu, L Mu Scientific reports 11 (1), 11738, 2021 | 77 | 2021 |
| A hybrid approach for El Niño prediction based on Empirical Mode Decomposition and convolutional LSTM Encoder-Decoder S Wang, L Mu, D Liu Computers & Geosciences 149, 104695, 2021 | 37 | 2021 |
| Improved transformer model for enhanced monthly streamflow predictions of the Yangtze River C Liu, D Liu, L Mu Ieee Access 10, 58240-58253, 2022 | 32 | 2022 |
| An innovative coupling technique for integrating oil spill prediction model with finite volume method-based ocean model D Liu, L Mu, S Ha, S Wang, E Zhao Marine Pollution Bulletin 185, 114242, 2022 | 6 | 2022 |
| Research on sunken & submerged oil detection and its behavior process under the action of breaking waves based on YOLO v4 algorithm S Fang, L Mu, S Jia, K Liu, D Liu Marine Pollution Bulletin 179, 113682, 2022 | 6 | 2022 |
| Parameterization modeling for wind drift factor in oil spill drift trajectory simulation based on machine learning D Liu, Y Li, L Mu Frontiers in Marine Science 10, 1222347, 2023 | 3 | 2023 |
| Streamflow prediction of the Yangtze River base on deep learning neural networks: impact of the El Niño–southern oscillation S Ha, D Liu, L Mu | 2 | 2021 |
| Combining artificial intelligence and laboratory experiments to explore behavior process of sunken and submerged oil: A typical oil drift and diffusion detection technology S Fang, L Mu, S Jia, K Liu, D Liu Journal of Cleaner Production 367, 133026, 2022 | 1 | 2022 |
| ResNet Based Parallel Intelligent System Design for Marine Search and Rescue Z Su, D Liu, L Mu 2020 IEEE 22nd International Conference on High Performance Computing and …, 2020 | 1 | 2020 |
| Effective Storm Surge Evacuation Planning Coupling Risk Assessment and DRL: A Case Study of Daya Bay Petrochemical Industrial Zone C Liu, Y Li, W Li, H Qin, L Mu, S Wang, D Liu, K Zhou EGUsphere 2024, 1-29, 2024 | | 2024 |
| Deep learning technique for examining the mechanism, transport, and behavior of oil-related hazardous material caused by wave breaking and turbulence S Fang, M Lin, S Jia, K Liu, D Liu Environmental Research Letters 17 (10), 104058, 2022 | | 2022 |
| Detection of the Sinking State of Liquid Oil in Breaking Waves Based on Synthesized Data: A Behavior Process Study of Sunken and Submerged Oil S Fang, L Mu, K Liu, D Liu Journal of Marine Science and Engineering 10 (5), 604, 2022 | | 2022 |
| Effective Storm Surge Evacuation Planning Coupling GIS and Drl: A Case Study of Daya Bay Petrochemical Industrial Zone C Liu, Y Li, H Qin, L Mu, S Wang, D Liu, K Zhou Available at SSRN 4456497, 0 | | |
