Analyzing Land Use Change and Climate Data to Forecast Energy Demand for a Smart Environment

Energy is essential for the sustainable development of nations. Increasing population growth, along with expected increases in duration and intensity of extreme weather, can increase energy demands. There is the potential for further interruption if companies do not appropriately account for an increase in demand, especially with the state and federal agencies implementing a transition to clean energy production by the end of the decade. In order to assess energy demand with changing variables, we conduct energy demand analysis in a moderate emissions scenario in the residential sector that consumes the most energy of all energy sectors. We assess changes in energy demand by comparing results from the data mining / machine learning techniques of Support Vector Machines (SVM) and Artificial Neural Network (ANN). Our results are helpful in contributing to sustainable energy goals in line with smart environment initiatives via greenness and energy efficiency.