Improving the forecasting accuracy of monthly runoff time series of the Brahmani River in India using a hybrid deep learning model

Improving the forecasting accuracy of monthly runoff time series of the Brahmani River in India using a hybrid deep learning model

Accurate prediction of monthly runoff is critical for effective water resource management and flood forecasting in river basins. In this study, we developed a hybrid deep learning (DL) model, Fourier transform long short-term memory (FT-LSTM), to improve the prediction accuracy of monthly discharge...

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Bibliographic Details
Main Authors: Sonali Swagatika, Jagadish Chandra Paul, Bibhuti Bhusan Sahoo, Sushindra Kumar Gupta, P. K. Singh
Format: Article
Language:English
Published: IWA Publishing 2024-01-01
Series:Journal of Water and Climate Change
Subjects:
forecasting
gru
lstm
rnn
runoff
Online Access:http://jwcc.iwaponline.com/content/15/1/139

Internet

http://jwcc.iwaponline.com/content/15/1/139

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