Sales Volume Forecasting Decision Models

The sales volume forecasting process is a critical one for most businesses, also a difficult area of management. Most of researches and companies use the statistical methods, regression analysis, or sophisticated computer simulations to analyze the sales volume forecasting. The theory of support vector regression (SVR) is introduced in this paper. And genetic algorithms (GAs) are adopted to optimize free parameters of support vector regression. In this study, GA-SVR is applied to predict sales volume. The experimental results indicate that GA-SVR model proposed in this paper can achieve better forecasting accuracy and performance than traditional SVR and artificial Neural Network forecasting models.