Ramiz Gorkem Birdal*
CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4015-4028, 2024, DOI:10.32604/cmc.2024.048324
Abstract Maintaining a steady power supply requires accurate forecasting of solar irradiance, since clean energy resources do not provide steady power. The existing forecasting studies have examined the limited effects of weather conditions on solar radiation such as temperature and precipitation utilizing convolutional neural network (CNN), but no comprehensive study has been conducted on concentrations of air pollutants along with weather conditions. This paper proposes a hybrid approach based on deep learning, expanding the feature set by adding new air pollution concentrations, and ranking these features to select and reduce their size to improve efficiency. In order to improve the accuracy… More >
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