Modelling energy consumption of the Jordanian transportation sector: the application of multivariate linear regression and adaptive neuro-fuzzy techniques - Mazin Obaidat; Amr M. Obeidat; Ahmed Al-Ghandoor; Mohammad A. Gharaibeh; Hesham A. Almomani (International Journal of Sustainable Energy, 2019)
Studying the current level of energy consumed by the transportation sector in Jordan is a top priority and an important variable when it comes to modelling accurate projections of future consumption in order to monitor Jordan's sustainable development. This study compares two methods for modelling energy consumption within the Jordanian transportation sector: a multivariate linear regression model and a Neuro-fuzzy model. Within these two paradigms, energy consumption is modelled as a function of a number of factors such as: vehicles number, level of income and ownership, and fuel prices. A parallelism between the two models is highlighted providing a precise simulation for the energy consumption in the Jordanian transportation sector. The comparison proposes that when it comes to forecasting, the performance of the neuro-fuzzy model exceeds that of the multivariate linear regression model.