Abstract :
This study explores the possibility of developing a prediction model using artificial neural networks (ANN), which could be used to
estimate monthly average daily global solar irradiation on a horizontal surface for locations in Uganda based on weather station data:
sunshine duration, maximum temperature, cloud cover and location parameters: latitude, longitude, altitude. Results have shown good
agreement between the estimated and measured values of global solar irradiation. A correlation coefficient of 0.974 was obtained with
mean bias error of 0.059 MJ/m2 and root mean square error of 0.385 MJ/m2. The comparison between the ANN and empirical method
emphasized the superiority of the proposed ANN prediction model.
2007 Elsevier Ltd. All rights reserved
