Development of Grey Machine Learning Models for Forecasting of Energy Consumption, Carbon Emission and Energy Generation for the Sustainable Development of Society

Energy is an important denominator for evaluating the development of any country. consumption, energy production and steps towards obtaining green are factors sustainable development. With advent forecasting technologies, these can be accessed earlier, planning path chalked out. Forecasting technologies pertaining to grey systems in spotlight due fact that they do not require many data points. In this work, optimized model with machine learning architecture a polynomial realization was employed predict power generation, consumption CO2 emissions. A nonlinear kernel taken recently published algorithm, augmented crow search algorithm (ACSA), prediction. It found as compared conventional models, proposed framework yields better results terms accuracy.