Prediction of Solar Radiation Using Artificial Neural Network

Most solar applications and systems can be reliably used to generate electricity power in many homes offices. Recently, there is an increase required that found not only generation but other such as distillation, water heating, heating of buildings, meteorology producing conversion energy. Prediction radiation very significant order accomplish the previously mentioned objectives. In this paper, main target present algorithm predict hourly activity radiation. Using a dataset consists temperature air, time, humidity, wind speed, atmospheric pressure, direction data, Artificial Neural Network (ANN) model constructed effectively forecast using available weather data. Two models are created efficiently create system capable interpreting patterns through supervised learning data correct amount atmosphere. The results two statistical indicators: Mean Absolute Error (MAE) Squared (MSE) performed compared with observed predicted These were able efficient predictions sufficient performance accuracy.