Streamflow classification by employing various machine learning models for peninsular Malaysia

• Main Authors: AlDahoul N., Momo M.A., Chong K.L., Ahmed A.N., Huang Y.F., Sherif M., El-Shafie A.
• Other Authors: 56656478800
• Format: Article
• Published: Nature Research 2024
• Subjects: article; forecasting; Johor; Kelantan; machine learning; Malaysia; Melaka; Perlis; prediction; river; Selangor; support vector machine; time series analysis; uncertainty
• Institution: Universiti Tenaga Nasional

Due to excessive streamflow (SF), Peninsular Malaysia has historically experienced floods and droughts. Forecasting streamflow to mitigate municipal and environmental damage is therefore crucial. Streamflow prediction has been extensively demonstrated in the literature to estimate the continuous val...