研究论文
Multi-scale Spatio-temporal graph neural network for enhanced water demand forecasting
Ang Xu, Tuqiao Zhang, Xuanpeng Zhang, Yu Shao, Tingchao Yu, Shipeng Chu, Lijuan Qian
Zhejiang University China Jiliang University
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逐年被引趋势
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1126
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11
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3.21
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同类平均 = 1
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物理Hydrological Forecasting Using AI
Traffic Prediction and Management Techniques · Water Systems and Optimization
参考文献 43
Statistical modeling of daily urban water consumption in Hong Kong: Trend, changing patterns, and forecast
被引 115Jefferson See Wong, Qiang Zhang, Yongqin David Chen · Water Resources Research · 2010
Urban Water Demand Forecasting: Review of Methods and Models
被引 443Emmanuel Amponsah Donkor, Thomas A. Mazzuchi, Refik Soyer · Journal of Water Resources Planning and Management · 2012
Forecasting operational demand for an urban water supply zone
被引 187Senlin Zhou, Thomas A. McMahon, A Walton · Journal of Hydrology · 2002
此处列出前 3 条
引用本文 11
MSTRFormer: A multi-factor daily runoff forecasting model integrating adaptive graph convolution and linear attention
被引 4Wenchuan Wang, C. SHI, Yi-yang Wang · Applied Soft Computing · 2026
Physics-informed graph inference and prediction for global state estimation in water distribution networks
被引 1Yacan Man, Xiao Hu Zhou, Wenchong Tian · Water Research · 2026
A spatiotemporal deep learning approach to improve real-time effluent quality prediction in wastewater treatment plant
被引 0Binru Yang, Jiaxi Wang · Results in Engineering · 2026
按被引量排序，此处列出前 3 条