Akademik Veri Yönetim Sistemi
3rd International Symposium of Scientific Research and Innovative Studies, Balıkesir, Türkiye, 15 - 18 Mart 2023, ss.258-268
Solar radiation emitted as electromagnetic radiation emitted by the sun can be used
for heating, conversion to electrical energy and different energy use. In this context, the
appropriate periods of solar energy and how much is important. In this way, it can be calculated
how much energy can be produced with the existing solar energy. In this study, the rate of
radiation emitted from solar energy was predicted by using a dataset including temperature,
humidity, pressure, wind direction and speed, and sunrise and sunset variables covering a fourmonth period. In this context, ridge regression, linear regression, lasso, random forest, support
vector regressor, decision tree regressor and gradient boosting regressor methods, which are
machine learning techniques, were used. In addition to these methods, a method consisting of
a combination of bagging tree, random forest and decision tree was added and the best
prediction method of solar radiation was tried to be selected among nine different methods.
According to the results obtained, it was seen that the best result was obtained with the stacking
model consisting of a combination of random forest regressor and decision tree regressor.