Energy Requirement and Availability Analysis in the Indian Subcontinent using Machine Learning

Efficient energy data analysis and then prediction can be especially beneficial in the Indian Subcontinent with its ever-growing need and industrial expansion. The authors developed and compared three different machine learning (ML) models namely, Linear Regression, Decision Tree Regression and Random Forest Regressor for energy requirement against energy availability analysis restricted to the mentioned region. The models achieved an R 2 value of 99.76%, 99.58% and 99.72% respectively. Observations regarding the results obtained were discussed along with a review of related works. Finally, the authors provided some pointers for future research.