Daily diffuse solar radiation estimation using adaptive neuro-fuzzy inference system technique

Abstract

In this study, an adaptive neuro-fuzzy inference system (ANFIS) model is proposed for the prediction of daily diffuse solar radiation. Eight factors including month of the year, sunshine duration, barometric pressure, relative humidity, mean temperature, wind speed, rainfall and daily global solar radiation are used as the inputs, while the daily diffuse solar radiation is the output. To compare the performance of the ANFIS, artificial neural network (ANN) and Iqbal models, two statistical benchmark indices, root-mean-squared error (RMSE) and coefficient of determination (R²), are adopted in this study. The results show that the proposed ANFIS model has potential in accurately predicting the daily diffuse solar radiation.