Artificial neural networks and sales demand forecasting application in the automotive industry

In this study, recently, an estimation method frequently used Artificial Neural Networks have attempted sales demand forecast of engine bearing. Because a lot of factors that affect the sales demand, there is a need for accurate and reliable estimates. At the beginning of the existence of objective company comes to provide continuity with making profits and to satisfy employees and customers. The most effective way in winning customer satisfaction is to send the goods and services demanded by customers timely when the customer wants. Orders, to send the requested time, it is first necessary to estimate how much the order in which period may be. Factors affecting the engine bearing sales demand are dolar exchange rates, GDP, number of tractor parking, the number of vehicles produced, the number of exports, interest rate, CPI and PPI. The fact that the neural network also produces the results were statistically analyzed how much reflects. Artificial neural network from the obtained results were compared to those of regression and time series and the results found with artificial neural networks, gave close results more real than others. Keywords: Sales Forecast, Artificial Neural Networks, Regression Analysis