所蔵: Sediment load prediction in Johor river: deep learning versus machine learning models

Sediment load prediction in Johor river: deep learning versus machine learning models

Sediment transport is a normal phenomenon in rivers and streams, contributing significantly to ecosystem production and preservation by replenishing vital nutrients and preserving aquatic life�s natural habitats. Thus, sediment transport prediction through modeling is crucial for predicting flood ev...

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書誌詳細
主要な著者:	Latif S.D., Chong K.L., Ahmed A.N., Huang Y.F., Sherif M., El-Shafie A.
その他の著者:	57216081524
フォーマット:	論文
出版事項:	Springer Science and Business Media Deutschland GmbH 2024
主題:	Artificial neural network (ANN) Long short-term memory (LSTM) Sediment transport prediction Support vector machine (SVM) Johor Johor River Malaysia West Malaysia Brain Floods Forecasting Learning systems Long short-term memory Rivers Sediment transport Water supply Artificial neural network Load predictions Machine learning models Machine-learning Neural network and support vector machines Sediment loads Support vector machine Support vectors machine artificial neural network autocorrelation comparative study computer simulation fluvial deposit machine learning model validation numerical model prediction sediment transport support vector machine Support vector machines
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Sediment load prediction in Johor river: deep learning versus machine learning models

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