基于BP神经网络的烟叶醇化感官质量仿真模拟

Simulation of sensory quality of tobacco leaf alcoholization based on BP neural network

通过建立烟叶醇化感官质量的预测模型,用于预测烟叶醇化过程中的感官变化,突破烟叶养护工作传统以经验指导烟叶库存周转和配方使用。选取4个仓库中18个不同样品烟叶在间隔6个月,共36个月自然醇化后的醇化感官评分作为初始样本。通过因子分析,划分出烟叶醇化度等级,再进行BP神经网络训练,经检验表明此模型应用于预测烟叶醇化感官质量性能较好,均方误差最大值(MSE)为1.00E-06,预测可知第42个月烟叶醇化度等级仅凉山会理C3F不合格。

Establish a prediction model for sensory quality of tobacco leaf alcoholization,which is used to predict sensory changes in the process of tobacco leaf alcoholization process,breaking through the traditional empirical method to guide tobacco leaf inventory turnover and formulation use.In this paper,18 alcoholic sensory scores of the 18 different samples in 4 warehouses were taken as initial samples at intervals of 6 months,totally 36 months.Firstly,Through factor analysis,the tobacco alcoholization level is divided,and then to perform BP neural network test and prediction,the results show that this model is feasible and effective for predicting the sensory quality of tobacco leaf alcoholization,and Mean Squared Error(MSE)is 1.00E-06.It is predicted that the degree of alcoholification of tobacco leaves in the 42th month can only be seen as a failure of Liangshan Huili C3F。