A PREDICTION APPROACH BASED ON ARTIFICIAL NEURAL NETWORKS WITH CONSIDERATION OF ENVIRONMENTAL AND ECONOMIC INDICATORS FOR CAR SALES IN TURKEY
Journal Title: Endüstri Mühendisliği - Year 2015, Vol 26, Issue 3
Abstract
In this study, car sales forecasting for different segments and brands has been aimed considering both environmental and economic indicators. For this purpose, segments and brands of products, past sales quantity, interest rate, gross national product, CO2 emission, fuel consumption and fuel price have been selected as prediction inputs. Using those prediction inputs, artificial neural network model has been recommended to predict car sales. Dataset which is used for prediction, includes car sales of three different brands and three different segments of each brand between the years of 2008-2012. For the artificial neural network model, feed neural network model (FFNN) has been applied. Levenberg-Marquadt algorithm has been used for training of the model. Results of artificial neural networks and linear regression have been compared with each other. Ultimately, It has been acquired that artificial neural network model has more accurate prediction results than linear regression model.
Authors and Affiliations
Yusuf KUVVETLİ, Cansu Dağsuyu, Murat OTURAKÇI
Keywords
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