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Accurate stream flow quantification and prediction are essential for the local and global planning and management of basins to cope with climate change. The ability to forecast streamflow is crucial, as it can help mitigate flood risks. Long-term stream flow data records are needed for hydropower plant construction, flood prediction, watershed management, and long-term water supply use. An accurate assessment of streamflow is considered as very challenging and critical tasks. A new predicting model is developed in this research, combining the technique of sunflower optimization (SFA) as an evolutionary algorithm with the multi-layer perceptron (MLP) algorithm to predict streamflow in Malaysia's Jam Seyed Omar (JSO) and Muda Di Jeniang (MDJ) stations. Principal component analysis (PCA) was performed on Q (t) (t: the number of the current day) before model creation to pick essential inputs for a maximum of …