Abstract
Due to the contradiction between energy production and demand in the current energy crisis, power consumption (PC) is crucial to the world economy. Energy industry can improve power system control and energy usage by using machine learning (ML) models, which are widely acknowledged as a precise and computationally efficient prediction solution. For the purpose of projecting energy consumption and performance, machine learning (ML) techniques and artificial intelligence (AI) have been suggested recently. The various machine learning (ML) techniques i.e. artificial neural networks (ANN), support vector machines (SVM), Gaussian-based regressions and Fuzzy logic etc. that have been frequently used in predicting and enhancing energy performance are reviewed in-depth in this research.
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