A new soft computing model for daily streamflow forecasting
Date
2021
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Abstract
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.
Description
Keywords
MLP, Streamflow, Sunflower optimization, Principal component analysis
Citation
Sammen, S. S., Ehteram, M., Abba, S. I., Abdulkadir, R. A., Ahmed, A. N., & El-Shafie, A. (2021). A new soft computing model for daily streamflow forecasting. Stochastic Environmental Research and Risk Assessment, 35(12), 2479-2491.