Application of Long Short-Term Memory (LSTM) Neural Network for Flood Forecasting

Application of Long Short-Term Memory (LSTM) Neural Network for Flood Forecasting

Flood forecasting is an essential requirement in integrated water resource management. This paper suggests a Long Short-Term Memory (LSTM) neural network model for flood forecasting, where the daily discharge and rainfall were used as input data. Moreover, characteristics of the data sets which may...

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Bibliographic Details
Main Authors: Xuan-Hien Le, Hung Viet Ho, Giha Lee, Sungho Jung
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Water
Subjects:
flood forecasting
Artificial Neural Network (ANN)
Recurrent Neural Network (RNN)
Long Short-Term Memory (LSTM)
deep neural network
Da river
Online Access:https://www.mdpi.com/2073-4441/11/7/1387

Internet

https://www.mdpi.com/2073-4441/11/7/1387

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