Water Level Prediction of Riam Kanan Dam Using ConvLSTM, BPNN,
Gradient Boosting, and XGBoosting Stacking Framework
(CLBGXGBoostS)

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Water Level Prediction of Riam Kanan Dam Using ConvLSTM, BPNN, Gradient Boosting, and XGBoosting Stacking Framework (CLBGXGBoostS)

Research focuses on developing a water level prediction framework for the Riam Kanan Dam using an innovative stacking approach called ConvLSTM-BPNN-Gradient Boosting and Stacking XGBoost (CLBGXGBoostS), which combines the strengths of Convolutional Long Short-Term Memory (ConvLSTM), Backpropagati...

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Bibliographic Details
Main Authors:	Usman, Syapotro, Haldi, Budiman, M.Rezqy, Noor Ridha, Noor, Azijah
Format:	Article
Language:	English English
Published:	INTI International University 2024
Subjects:	QA75 Electronic computers. Computer science QA76 Computer software T Technology (General)
Online Access:	http://eprints.intimal.edu.my/2052/ http://eprints.intimal.edu.my/2052/1/jods2024_53.pdf http://eprints.intimal.edu.my/2052/2/593

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