Comparison of Deep Learning Techniques for River Streamflow Forecasting

Comparison of Deep Learning Techniques for River Streamflow Forecasting

Recently, deep learning (DL) models, especially those based on long short-term memory (LSTM), have demonstrated their superior ability in resolving sequential data problems. This study investigated the performance of six models that belong to the supervised learning category to evaluate the performa...

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Bibliographic Details
Main Authors:	Xuan-Hien Le, Duc-Hai Nguyen, Sungho Jung, Minho Yeon, Giha Lee
Format:	Article
Language:	English
Published:	IEEE 2021-01-01
Series:	IEEE Access
Subjects:	Bidirectional LSTM deep learning gated recurrent unit long short-term memory streamflow forecasting
Online Access:	https://ieeexplore.ieee.org/document/9423961/

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