Despite the worldwide population and economy expanding so quickly, an enormous increase in the demand for energy has been predicted. Therefore, it becomes crucial to supply electricity to consumers and companies in an efficient manner in order to reduce power loss. These energy losses throughout distribution of energy could be minimized by smart grids (SG). In order to deal with load forecasting, numerous forecasting methods have been developed, which is today an important and fundamental part of the processes involved in producing energy. Numerous Machine Learning (ML) approaches have been successfully used in smart grids (SGs) in order to increase the precision of consumer demand Download
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