Intercomparison of deep learning models in predicting streamflow patterns: insight from CMIP6

Intercomparison of deep learning models in predicting streamflow patterns: insight from CMIP6

Abstract This research was carried out to predict daily streamflow for the Swat River Basin, Pakistan through four deep learning (DL) models: Feed Forward Artificial Neural Networks (FFANN), Seasonal Artificial Neural Networks (SANN), Time Lag Artificial Neural Networks (TLANN) and Long Short-Term M...

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Bibliographic Details
Main Authors: Hamid Anwar, Afed Ullah Khan, Basir Ullah, Abubakr Taha Bakheit Taha, Taoufik Najeh, Muhammad Usman Badshah, Abdulnoor A. J. Ghanim, Muhammad Irfan
Format: Article
Language:English
Published: Nature Portfolio 2024-07-01
Series:Scientific Reports
Subjects:
Streamflow
Prediction
Deep learning
GCM
CMIP6
Online Access:https://doi.org/10.1038/s41598-024-63989-7

Internet

https://doi.org/10.1038/s41598-024-63989-7

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