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Predictor selection method for the construction of support vector machine (SVM)‐based typhoon rainfall forecasting models using a non‐dominated sorting genetic algorithm
Predictor selection method for the construction of support vector machine (SVM)‐based typhoon rainfall forecasting models using a non‐dominated sorting genetic algorithm
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Predictor selection method for the construction of support vector machine (SVM)‐based typhoon rainfall forecasting models using a non‐dominated sorting genetic algorithm

Yang, Tao‐Chang ; Yu, Pao‐Shan ; Lin, Kun‐Hsiang ; Kuo, Chen‐Min ; Tseng, Hung‐Wei

Meteorological applications, 2018-10, Vol.25 (4), p.510-522 [Periódico revisado por pares]

Chichester, UK: John Wiley & Sons, Ltd

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2
Incorporating large-scale atmospheric variables in long-term seasonal rainfall forecasting using artificial neural networks: an application to the Ping Basin in Thailand
Incorporating large-scale atmospheric variables in long-term seasonal rainfall forecasting using artificial neural networks: an application to the Ping Basin in Thailand
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Incorporating large-scale atmospheric variables in long-term seasonal rainfall forecasting using artificial neural networks: an application to the Ping Basin in Thailand

Babel, M. S. ; Sirisena, T. A. J. G. ; Singhrattna, N.

Hydrology Research, 2017-06, Vol.48 (3), p.867-882 [Periódico revisado por pares]

London: IWA Publishing

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3
Typhoon Rainfall Forecasting by Means of Ensemble Numerical Weather Predictions with a GA-Based Integration Strategy
Typhoon Rainfall Forecasting by Means of Ensemble Numerical Weather Predictions with a GA-Based Integration Strategy
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Typhoon Rainfall Forecasting by Means of Ensemble Numerical Weather Predictions with a GA-Based Integration Strategy

Wu, Ming-Chang ; Yang, Sheng-Chi ; Yang, Tsun-Hua ; Kao, Hong-Ming

Atmosphere, 2018-11, Vol.9 (11), p.425 [Periódico revisado por pares]

Basel: MDPI AG

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4
A Rainfall‐Runoff Model With LSTM‐Based Sequence‐to‐Sequence Learning
A Rainfall‐Runoff Model With LSTM‐Based Sequence‐to‐Sequence Learning
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A Rainfall‐Runoff Model With LSTM‐Based Sequence‐to‐Sequence Learning

Xiang, Zhongrun ; Yan, Jun ; Demir, Ibrahim

Water resources research, 2020-01, Vol.56 (1), p.n/a [Periódico revisado por pares]

Washington: John Wiley & Sons, Inc

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5
Flash Flood and Extreme Rainfall Forecast through One-Way Coupling of WRF-SMAP Models: Natural Hazards in Rio de Janeiro State
Flash Flood and Extreme Rainfall Forecast through One-Way Coupling of WRF-SMAP Models: Natural Hazards in Rio de Janeiro State
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Flash Flood and Extreme Rainfall Forecast through One-Way Coupling of WRF-SMAP Models: Natural Hazards in Rio de Janeiro State

da Cunha Luz Barcellos, Priscila ; Cataldi, Marcio

Atmosphere, 2020-08, Vol.11 (8), p.834 [Periódico revisado por pares]

Basel: MDPI AG

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6
Rainfall–runoff prediction at multiple timescales with a single Long Short-Term Memory network
Rainfall–runoff prediction at multiple timescales with a single Long Short-Term Memory network
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Rainfall–runoff prediction at multiple timescales with a single Long Short-Term Memory network

Gauch, Martin ; Kratzert, Frederik ; Klotz, Daniel ; Nearing, Grey ; Lin, Jimmy ; Hochreiter, Sepp

Hydrology and earth system sciences, 2021-04, Vol.25 (4), p.2045-2062 [Periódico revisado por pares]

Katlenburg-Lindau: Copernicus GmbH

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7
Enhanced Meiyu‐Baiu Rainfall in Early Summer 2020: Aftermath of the 2019 Super IOD Event
Enhanced Meiyu‐Baiu Rainfall in Early Summer 2020: Aftermath of the 2019 Super IOD Event
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Enhanced Meiyu‐Baiu Rainfall in Early Summer 2020: Aftermath of the 2019 Super IOD Event

Takaya, Yuhei ; Ishikawa, Ichiro ; Kobayashi, Chiaki ; Endo, Hirokazu ; Ose, Tomoaki

Geophysical research letters, 2020-11, Vol.47 (22), p.n/a [Periódico revisado por pares]

Washington: John Wiley & Sons, Inc

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8
Record‐Breaking Meiyu Rainfall Around the Yangtze River in 2020 Regulated by the Subseasonal Phase Transition of the North Atlantic Oscillation
Record‐Breaking Meiyu Rainfall Around the Yangtze River in 2020 Regulated by the Subseasonal Phase Transition of the North Atlantic Oscillation
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Record‐Breaking Meiyu Rainfall Around the Yangtze River in 2020 Regulated by the Subseasonal Phase Transition of the North Atlantic Oscillation

Liu, Boqi ; Yan, Yuhan ; Zhu, Congwen ; Ma, Shuangmei ; Li, Jianying

Geophysical research letters, 2020-11, Vol.47 (22), p.n/a [Periódico revisado por pares]

Washington: John Wiley & Sons, Inc

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9
Deep learning rainfall–runoff predictions of extreme events
Deep learning rainfall–runoff predictions of extreme events
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Deep learning rainfall–runoff predictions of extreme events

Frame, Jonathan M ; Kratzert, Frederik ; Klotz, Daniel ; Gauch, Martin ; Shelev, Guy ; Gilon, Oren ; Qualls, Logan M ; Gupta, Hoshin V ; Nearing, Grey S

Hydrology and earth system sciences, 2022-07, Vol.26 (13), p.3377-3392 [Periódico revisado por pares]

Katlenburg-Lindau: Copernicus GmbH

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10
Real‐Time Flood Forecasting Based on a High‐Performance 2‐D Hydrodynamic Model and Numerical Weather Predictions
Real‐Time Flood Forecasting Based on a High‐Performance 2‐D Hydrodynamic Model and Numerical Weather Predictions
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Real‐Time Flood Forecasting Based on a High‐Performance 2‐D Hydrodynamic Model and Numerical Weather Predictions

Ming, Xiaodong ; Liang, Qiuhua ; Xia, Xilin ; Li, Dingmin ; Fowler, Hayley J.

Water resources research, 2020-07, Vol.56 (7), p.n/a [Periódico revisado por pares]

Washington: John Wiley & Sons, Inc

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