Abstract
Objective: The simulation and prediction model between the process of silk making and the quality of finished tobacco was established. Methods: The average influence value method was used to screen the process parameters in the process of making silk, and then a simulation model of the key process parameters of the silk and the quality of the final tobacco was constructed through the Back-Propagation neural network. Results: Comparing the simulated data with the measured data, the average relative error of the simulated prediction of the filling value was 3.16%; the average relative error of the simulated prediction of the whole cut rate was 0.67%; the average relative error of the simulated prediction of the broken cut rate was 5.33%. Conclusions: The relative error between the data predicted by this model and the real data is small, and the accuracy is high, which provides a theoretical basis and simulation method for the optimization of process parameters in the tobacco process.
Publication Date
12-28-2021
First Page
161
Last Page
166,214
DOI
10.13652/j.issn.1003-5788.2021.12.027
Recommended Citation
Ming, ZHUO; Peng, WANG; and Kai-kui, WANG
(2021)
"Prediction model building for finished tobacco quality based on MIV-BP neural network,"
Food and Machinery: Vol. 37:
Iss.
12, Article 27.
DOI: 10.13652/j.issn.1003-5788.2021.12.027
Available at:
https://www.ifoodmm.cn/journal/vol37/iss12/27
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