Enhancing the prediction accuracy of data-driven models for monthly streamflow in Urmia Lake Basin based upon the autoregressive conditionally heteroskedastic time-series model

• Main Authors: Attar N.F., Pham Q.B., Nowbandegani S.F., Rezaie-Balf M., Fai C.M., Ahmed A.N., Pipelzadeh S., Dung T.D., Nhi P.T.T., Khoi D.N., El-Shafie A.
• Other Authors: 57203768412
• Format: Article
• Published: MDPI AG 2023

Hydrological modeling is one of the important subjects in managing water resources and the processes of predicting stochastic behavior. Developing Data-Driven Models (DDMs) to apply to hydrological modeling is a very complex issue because of the stochastic nature of the observed data, like seasonali...