An Intelligent Model to Forecast Energy Demand Using Fused Machine Learning Approaches

Abstract

The use of Internet of Things (IoT) for smart energy management is becoming increasingly popular as it allows for better control and management of energy consumption. It provides a soft communication platform to ensure a fair distribution of energy across users, as well as improved management of the entire electric system by suppliers. In this research, an intelligent model is developed to accurately forecast energy demands by employing a fused machine learning approach, which combines Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms. Machine learning (ML) is a sub-field of Artificial Intelligence (AI) that utilizes predictive algorithms to process the electrical efficiency and response of moderate energy production, transmission, and consumption. The fusion approach performs point-wise fusion of forecasts from different estimators, weighted by their confidence over predictions. With the help of this fused machine learning approach, the proposed model is expected to exhibit improved performance when predicting energy demands