A practical temporal transfer learning model for multi-step water quality index forecasting using A CNN-coupled dual-path LSTM network

A practical temporal transfer learning model for multi-step water quality index forecasting using A CNN-coupled dual-path LSTM network

Study region: Klang River, Malaysia. Study focus: This study presents a multi-step ahead water quality index (WQI) forecasting framework in Klang River to address persistent challenges such as missing data and seasonally variable hydrological patterns. A hybrid deep learning architecture was develop...

Full description

Saved in:
Bibliographic Details
Main Authors: Kok Poh Wai, Chai Hoon Koo, Yuk Feng Huang, Woon Chan Chong, Ahmed El-Shafie, Mohsen Sherif, Ali Najah Ahmed
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:Journal of Hydrology: Regional Studies
Subjects:
Water quality index
Multi-step ahead forecasting
Temporal transfer learning
Convolutional neural network
Long short-term memory
Rolling forecasting
Online Access:http://www.sciencedirect.com/science/article/pii/S2214581825003787
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://www.sciencedirect.com/science/article/pii/S2214581825003787

Similar Items