A Detailed Review of Energy-Aware Machine Learning Systems
The review paper provides a brief introduction of energy-aware systems incorporating Machine learning models for forecasting energy consumption in order to improve the energy efficiency in energy-related applications. Existing literature provides a detailed analysis of various energy-aware approaches based on machine learning mechanisms. The study also covers the review of different ML models such as ANN, SVM, Decision Tree, DCNN and Ensemble learning technique. A comparative analysis is presented which incorporates the objectives of various energy-aware applications and ML models and the observations and future scope are tabulated.