| A review of data-driven approaches for burst detection in water distribution systems Y Wu, S Liu Urban Water Journal 14 (9), 972-983, 2017 | 189 | 2017 |
| Short-term water demand forecast based on deep learning method G Guo, S Liu, Y Wu, J Li, R Zhou, X Zhu Journal of Water Resources Planning and Management 144 (12), 04018076, 2018 | 140 | 2018 |
| Burst detection in district metering areas using a data driven clustering algorithm Y Wu, S Liu, X Wu, Y Liu, Y Guan Water research 100, 28-37, 2016 | 123 | 2016 |
| Burst detection in district metering areas using deep learning method X Wang, G Guo, S Liu, Y Wu, X Xu, K Smith Journal of Water Resources Planning and Management 146 (6), 04020031, 2020 | 65 | 2020 |
| Leakage detection in water distribution systems based on time–frequency convolutional neural network G Guo, X Yu, S Liu, Z Ma, Y Wu, X Xu, X Wang, K Smith, X Wu Journal of Water Resources Planning and Management 147 (2), 04020101, 2021 | 59 | 2021 |
| Using correlation between data from multiple monitoring sensors to detect bursts in water distribution systems Y Wu, S Liu, K Smith, X Wang Journal of Water Resources Planning and Management 144 (2), 04017084, 2018 | 40 | 2018 |
| Towards greater socio-economic equality in allocation of wastewater discharge permits in China based on the weighted Gini coefficient Q Yuan, N McIntyre, Y Wu, Y Liu, Y Liu Resources, Conservation and Recycling 127, 196-205, 2017 | 36 | 2017 |
| Reducing energy use for water supply to China’s high-rises K Smith, S Liu, Y Liu, Y Liu, Y Wu Energy and Buildings 135, 119-127, 2017 | 26 | 2017 |
| Distance-based burst detection using multiple pressure sensors in district metering areas Y Wu, S Liu, X Wang Journal of Water Resources Planning and Management 144 (11), 06018009, 2018 | 19 | 2018 |
| Burst detection by analyzing shape similarity of time series subsequences in district metering areas Y Wu, S Liu Journal of Water Resources Planning and Management 146 (1), 04019068, 2020 | 18 | 2020 |
| Bridging hydraulics and graph signal processing: A new perspective to estimate water distribution network pressures X Zhou, S Liu, W Xu, K Xin, Y Wu, F Meng Water Research 217, 118416, 2022 | 12 | 2022 |
| Resilience evaluation for water distribution system based on partial nodes’ hydraulic information X Yu, Y Wu, X Zhou, S Liu Water Research 241, 120148, 2023 | 5 | 2023 |
| A weighting strategy to improve water demand forecasting performance based on spatial correlation between multiple sensors Y Wu, X Wang, S Liu, X Yu, X Wu Sustainable Cities and Society 93, 104545, 2023 | 5 | 2023 |
| Improved machine learning leak fault recognition for low-pressure natural gas valve M Liu, X Lang, S Li, L Deng, B Peng, Y Wu, X Zhou Process Safety and Environmental Protection 178, 947-958, 2023 | 3 | 2023 |
| Hybrid method for enhancing acoustic leak detection in water distribution systems: Integration of handcrafted features and deep learning approaches Y Wu, X Ma, G Guo, Y Huang, M Liu, S Liu, J Zhang, J Fan Process Safety and Environmental Protection 177, 1366-1376, 2023 | 3 | 2023 |
| A review of graph and complex network theory in water distribution networks: Mathematical foundation, application and prospects X Yu, Y Wu, F Meng, X Zhou, S Liu, Y Huang, X Wu Water Research, 121238, 2024 | 2 | 2024 |
| Modeling Indirect Greenhouse Gas Emissions Sources from Urban Wastewater Treatment Plants: Integrating Machine Learning Models to Compensate for Sparse Parameters with Abundant … Y Huang, Y Xie, Y Wu, F Meng, C He, H Zou, X Wang, A Shui, S Liu Environmental Science & Technology 57 (48), 19860-19870, 2023 | | 2023 |
