Prediction of Rainfall Using Hybrid SVM-HHO Model

Abstract Rainfall modeling is considered a need of the hour in order to understand, control, and monitor quality quantity water resources. Modeling rainfall one key components meteorological engineering process. Hydrological climatological studies require accurate estimation effectively manage Thus, adopting an advanced, reliable, intelligent model for forecasting will be great value resources engineering. The present study tried establish hybrid with combination Support Vector Machine (SVM) Harris Hawks Optimization (SVM-HHO) predicting time series Cachar district located Assam, India. predictive performance models examined based on statistical analysis. Statistical measures like root mean squared error (RMSE) coefficient correlation (CC) used evaluate model. It observed from obtained results that proposed exhibited least RMSE 20.29, highest CC 0.9714, during testing period. Findings this confirm optimisation strategy can regarded as powerful tool achieving better generalisation capability higher accurateness.