Reservoir evaporation prediction modeling based on artificial intelligence methods

Forecasting; Network architecture; Radial basis function networks; Tropics; Artificial intelligence methods; Climatic conditions; Climatic parameters; Prediction accuracy; Prediction model; Radial basis function neural networks; Support vector regression (SVR); Tropical environmental; Evaporation; a...

Full description

Saved in:
Bibliographic Details
Main Authors: Allawi M.F., Othman F.B., Afan H.A., Ahmed A.N., Hossain M.S., Fai C.M., El-Shafie A.
Other Authors: 57057678400
Format: Article
Published: MDPI AG 2023
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Forecasting; Network architecture; Radial basis function networks; Tropics; Artificial intelligence methods; Climatic conditions; Climatic parameters; Prediction accuracy; Prediction model; Radial basis function neural networks; Support vector regression (SVR); Tropical environmental; Evaporation; accuracy assessment; artificial intelligence; climate conditions; climate effect; evaporation; hydrological modeling; methodology; prediction; reservoir; tropical environment; Johor; Johor River; Layang Reservoir; Malaysia; West Malaysia