In the research, the role of three input selection techniques is evaluated on support vector
machine (SVM) performance for prediction of monthly stream flow. First, a SVM model is …

Monthly streamflow prediction can offer important information for optimal management of
water resources, flood mitigation, and drought warning. The semi-humid and semi-arid Wei …

This paper focuses on the development of a robust accurate streamflow prediction model by
balancing the abilities of exploitation and exploration to find the best parameters of a …

The present study compares the results of the Soil and Water Assessment Tool (SWAT) with
a Support Vector Machine (SVM) to predict the monthly streamflow of arid regions located in …

Some previous studies have proved that prediction models using traditional overall
decomposition sampling (ODS) strategy are unreasonable because the subseries obtained …

It is of great significance for operation, planning and dispatching of hydropower station to
predict monthly streamflow accurately. Therefore, the main goal of this study is to investigate …

Accurate and reliable prediction of streamflow is vital to the optimization of water resources
management, reservoir flood operations, catchment, and urban water management. In this …

The long-term streamflow forecasts are very significant in planing and reservoir operations.
The streamflow forecasts have to deal with a complex and highly nonlinear data patterns …

Among several components of the hydrology cycle, streamflow is one of the essential
process necessarily needed to be studied. The establishment of an accurate and reliable …

This paper investigates the ability of a least-squares support vector machine (LSSVM) model
to improve the accuracy of streamflow forecasting. Cross-validation and grid-search …