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[2] Yan, J.，Bárdossy, A.,Hörning, S.,Tao, T.，Conditional simulation of surface rainfall fields using modified phase annealing:Hydrology and Earth System Sciences,2020
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[3] Yan, J.，Li, F.,Bárdossy, A.，Tao, T.，Conditional simulation of spatial rainfall fields using random mixing: a study that implements full control over the stochastic process:Hydrology and Earth System Sciences,2021
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[4] Yan, J.，Tao, T.，Unsupervised anomaly detection in hourly water demand data using an asymmetric encoder-decoder model:Journal of Hydrology,2022
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[5] Li, F.，Yan, J.,Yan H.,Tao, T.，Duan H.，2D Modelling and energy analysis of entrapped air-pocket propagation and spring-like geysering in the drainage pipeline system:Engineering Applications of Computational Fluid Mechanics,2023
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[6] Zhu, W.，Yan H.,Wang J.,Li S.,Xin K.，Tao, T.,Yan, J.，An optimized LSTM-based approach applied to early warning and forecasting of ponding in the urban drainage system:Hydrology and Earth System Sciences,2023
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[7] Li, F.,Yan, J.，Xiong, X.,Yan, H.,Wang, L.，Tao, T.，GIS-based fuzzy comprehensive evaluation of urban flooding risk with socioeconomic-index system development:Environmental Science and Pollution Research,2022
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[9] Pu, Z.，Yan, J.,Tao, T.，Xin, K.，A hybrid Wavelet-CNN-LSTM Deep Learning model for short-term Urban Water Demand Forecasting:Frontiers of Environmental Science & Engineering,2023
