Study on the Forecasting Model of Cut Tobacco Filling Value Based on the Neural Network

The filling property is a vitally important physical index of cut tobacco. Due to the similar cigarette blending formulation and fixed technological process in cigarette production, relevant technological parameters have direct and significant influence on the filling value of cut tobacco. However, the relationship between the parameters and filling value is nonlinear, which makes it difficult to calculate filling values of cut tobacco directly based on the parameters. Therefore, seven most important technological parameters were selected, and the quantitative relation model between various parameters and the filling value was established with the BP neural network. Further, the model was designed with the BP neural network and trained through a large amount of data, so it could forecast the filling value according to the seven technological parameters and the relative error of forecasting results was about 4%. The establishment of the forecasting model provides a theoretical basis and simulation method for the mutual adjustment between the technological parameters and the filling value of cut tobacco.