This model employs an extended deep statistical comparison to compare the optimization performance of metaheuristics.

Optimization approaches require statistical comparisons hence, a novel approach has been addressed in reference. Likewise, for modeling of carbon dioxide emissions, different intelligent methods are discussed in reference. Applications of some optimized devices have also been investigated in the work. The research focused on the fact that the accuracy of prediction engines can be enhanced with the applications of optimization. The research showcased an amalgamation of a metaheuristic algorithm for parameter optimization of a whitening equation for market-clearing price prediction. Another important study integrating metaheuristics and grey mathematics was reported in reference. In this work, the authors provided a cubic polynomial-based realization for market-clearing price prediction. The latest research showcases the prediction of energy price with cubic polynomial realization.

Another very interesting approach pertaining to the forecasting of renewable energy consumption has been showcased in the reference. In reference, a novel Bernoulli grey model was presented for forecasting the consumption of renewable energy. Hence, during the last two decades, the research has focused on the development of a robust framework for grey architecture. These systems are difficult to model and sometimes yield pretty erroneous results. The systems having such partial known characteristics are characterized as grey systems.

Mathematica for machine learning