Abstract: Nowadays, Sales Forecasting is vital for any business in competitive atmosphere. For an accurate forecasting, correct variables should be considered. In this paper, we address these problems and a technique is proposed which combines two artificial intelligence algorithms in order to forecast future automobile sales in Saipa group which is a leading Automobile manufacturer in Iran. Anfis is used as the base technique which is combined with GA. GA is used in order to tune the Anfis results. Furthermore, sales forecasting is succeeded with annual data of years between 1990 and 2016. With this in mind, per capita income, inflation rate, housing, Importation, Currency Rate (USD), loan interest rate and automobile import tariffs are selected as effective variables in the proposed model. Finally, we compare our model with ANN model which is a well-known forecasting model.

Amirmahmood Vahabi, Shahrooz Seyyedi Hosseininia and Mahmood Alborzi. “A Sales Forecasting Model in Automotive Industry using Adaptive Neuro-Fuzzy Inference System(Anfis) and Genetic Algorithm(GA)”. International Journal of Advanced Computer Science and Applications (IJACSA) 7.11 (2016). http://dx.doi.org/10.14569/IJACSA.2016.071104

@article{Vahabi2016,
title = {A Sales Forecasting Model in Automotive Industry using Adaptive Neuro-Fuzzy Inference System(Anfis) and Genetic Algorithm(GA)},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071104},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071104},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {11},
author = {Amirmahmood Vahabi and Shahrooz Seyyedi Hosseininia and Mahmood Alborzi}
}