Water Level Prediction Model Applying a Long Short-Term Memory (LSTM)–Gated Recurrent Unit (GRU) Method for Flood Prediction

Water Level Prediction Model Applying a Long Short-Term Memory (LSTM)–Gated Recurrent Unit (GRU) Method for Flood Prediction

The damage caused by floods is increasing worldwide, and if floods can be predicted, the economic and human losses from floods can be reduced. A key parameter of flooding is water level data, and this paper proposes a water level prediction model using long short-term memory (LSTM) and a gated recur...

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Bibliographic Details
Main Authors:	Minwoo Cho, Changsu Kim, Kwanyoung Jung, Hoekyung Jung
Format:	Article
Language:	English
Published:	MDPI AG 2022-07-01
Series:	Water
Subjects:	water level prediction long short-term memory (LSTM) gated recurrent unit (GRU) meteorology data
Online Access:	https://www.mdpi.com/2073-4441/14/14/2221

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