Sales Forecasting Of Cigarette And Marketing Planning Based On Neural Network

With the rapid development of China’s tobacco economy, extent size of market demand for cigarettes determines the direction of the company’s decision-making,so the sales forecasting of cigarette is very important for the market competitiveness of China’s tobacco industry.On the one hand, because of the sales forecasting of cigarette is a time series prediction, so the paper introduces the knowledge about the time series prediction. More than that, cigarette sales have characteristics on non-linear, and coupled with the limitations of traditional statistical forecasting methods and neural network can reflect the characteristics of the nonlinear, the article be elaborated neural network theory. After that, I using clustering method to take a reasonable division on the company’s customers in the business lines and operating volume. Secondly, in order to be able to more performance the characteristics of cigarette sales in the long-term trends and short-term fluctuations, I established TBP(Trend Back Propagation) model and PBP(Period Back Propagation) model based on BP(Back Propagation) neural network according to the theoretical knowledge of the time series and neural network. Similarly, I established TRBF(Trend Radial Basis Function) model and PRBF(Period Radial Basis Function) model based on RBF(Radial Basis Function) neural network.Finally, I investigate the cigarette sales forecast model.On the other hand, found in the companies operating status of the problems and deficiencies, I accord to the company’s historical data and the status worked out a precision marketing program of work. And make a summary and outlook for the next work.