Debapriya Hazra, Wafa Shafqat, Yung-Cheol Byun*
CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3151-3167, 2022, DOI:10.32604/cmc.2022.020143
- 27 September 2021
Abstract Renewable and nonrenewable energy sources are widely incorporated for solar and wind energy that produces electricity without increasing carbon dioxide emissions. Energy industries worldwide are trying hard to predict future energy consumption that could eliminate over or under contracting energy resources and unnecessary financing. Machine learning techniques for predicting energy are the trending solution to overcome the challenges faced by energy companies. The basic need for machine learning algorithms to be trained for accurate prediction requires a considerable amount of data. Another critical factor is balancing the data for enhanced prediction. Data Augmentation is a… More >
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