A approach that combines different method (hybrid system) and ensemble learning technique to create a model that specifically focus on improving the accuracy of the time-series forecasting by effectively predicting the residuals.

Predicting future value based on historical data organized in a time-dependant sequence.

It involve combining multiple model to create a stronger, more robust model.

Advance renewable energy optimization and atmospheric science

Develop a hybrid forecasting system that leverages ensemble learning techniques to improve the performance of time series forecasting of solar irradiance by effectively modeling meteorological parameters.

Integrate AOD (Aerosol Optical Depth) data with other meteorological parameters can enhance time series prediction of solar irradiance.