Comparing Energy Demand Estimation Using Various Statistical Methods: The Case of Turkey

Authors : Yakup Murat Bulut, Zeki Yıldız

Pages : 237-244

View : 35 | Download : 8

Publication Date : 2016-06-20

Article Type : Research Paper

Abstract :Many engineers and scientists concern with future energy demand. They use many different statistical methods to estimate future energy demand such as multiple linear regression, neural networks, genetic algorithms and so on. In this paper, we propose ridge regression insert ignore into journalissuearticles values(RR); and partial least squares regression insert ignore into journalissuearticles values(PLSR); methods to estimate future energy demand. Because of the fact that variables, which are used in energy demand, are very collinear, ridge regression and partial least squares regression methods give more realistic results than least squares regression method. So, energy demand equations are developed based on RR and PLSR methods. Since, RR give better estimation, we estimate Turkey’s future energy demand based on RR method.
Keywords : Energy Demand, Energy Modeling, Biased Regression