烟丝物理指标对其回弹特性的影响研究

李晓; 郭朋玮; 周茂忠; 孙觅; 李劲锋; 张浩博; 李宜馨; 纪晓楠

doi:10.12187/2024.01.012

CN 41-1437/TS ISSN 2096-1553

烟丝物理指标对其回弹特性的影响研究

李晓 , 郭朋玮 , 周茂忠 , 孙觅 , 李劲锋 , 张浩博 , 李宜馨 , 纪晓楠

李晓, 郭朋玮, 周茂忠, 等. 烟丝物理指标对其回弹特性的影响研究[J]. 轻工学报, 2024, 39(1): 97-102. doi: 10.12187/2024.01.012

引用本文: 李晓, 郭朋玮, 周茂忠, 等. 烟丝物理指标对其回弹特性的影响研究[J]. 轻工学报, 2024, 39(1): 97-102. doi: 10.12187/2024.01.012

LI Xiao, GUO Pengwei, ZHOU Maozhong, et al. Research on the influence of physical indicators of cut tobacco on its rebound characteristics[J]. Journal of Light Industry, 2024, 39(1): 97-102. doi: 10.12187/2024.01.012

Citation: LI Xiao, GUO Pengwei, ZHOU Maozhong, et al. Research on the influence of physical indicators of cut tobacco on its rebound characteristics[J]. Journal of Light Industry, 2024, 39(1): 97-102. doi: 10.12187/2024.01.012

烟丝物理指标对其回弹特性的影响研究

1. 郑州轻工业大学烟草科学与工程学院, 河南郑州 450001;
2. 红云红河烟草(集团)有限责任公司, 云南昆明 650231;
3. 河南中烟工业有限责任公司技术中心, 河南郑州 450000

作者简介: 李晓(1966-),女,河南省南阳市人,郑州轻工业大学教授,主要研究方向为卷烟加工技术。E-mail:519389150@qq.com;

基金项目: 河南中烟工业有限责任公司重点项目(AW201911)
中国烟草总公司标准项目(2020QB0012)
中图分类号: TS45

Research on the influence of physical indicators of cut tobacco on its rebound characteristics

1. College of Tobacco Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou 450001, China;
2. Hongyun Honghe Tobacco (Group) Co., Ltd., Kunming 650231, China;
3. Technology Center, Henan Zhongyan Industry Co., Ltd., Zhengzhou 450000, China
Received Date: 2023-04-26
Accepted Date: 2023-06-25

CLC number: TS45

摘要: 以5种牌号常规卷烟成品烟丝为研究对象,采用多重线性回归分析方法研究烟丝物理指标对其回弹特性的影响规律,并构建基于BP神经网络的烟丝回弹特性预测模型。结果表明:烟丝物理指标对烟丝回弹特性的影响程度从大到小依次为碎丝率>中丝率>长丝率>填充值>弹性>含水率,其中,中丝率、长丝率、弹性、含水率与烟丝回弹特性呈正相关关系,碎丝率、填充值与烟丝回弹特性呈负相关关系;所构建的BP神经网络预测模型,测试集预测值与真实值比对R²为0.965 7,总体模型精度达到98.10%,烟丝回弹特性预测值与实测值之间的差异较小,模型具有较高的预测准确性和可靠性,可用于烟丝回弹特性的精确估算。
- 烟丝物理指标 /
- 回弹特性 /
- 多重线性回归分析 /
- BP神经网络
Abstract: Using 5 grades of conventional cigarette finished tobacco as the research object, multiple linear regression analysis method was used to study the influence of physical indicators of cut tobacco on its rebound characteristics, and a prediction model for tobacco rebound characteristics based on BP neural network was constructed. The results showed that the degree of influence of physical indicators of cut tobacco on the rebound characteristics of tobacco was ranked from large to small as follows: broken tobacco rate>medium tobacco rate>long tobacco rate>filling value>elasticity>moisture content. Among them, medium tobacco rate, long tobacco rate, elasticity, and moisture content were positively correlated with the rebound characteristics of tobacco, while broken tobacco rate and filling value were negatively correlated with the rebound characteristics of tobacco. In the constructed BP neural network prediction model, the comparison between the predicted value of the test set and the true value R² was 0.965 7, the overall model accuracy reached 98.10% . The difference between the predicted and measured values of cut tobacco rebound characteristics was small, and the model had high prediction accuracy and reliability, which could be used for accurate estimation of cut tobacco rebound characteristics.
- physical indicator of cut tobacco /
- rebound characteristics /
- multiple linear regression analysis /
- BP neural network
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李晓, 郭朋玮, 周茂忠, 等. 烟丝物理指标对其回弹特性的影响研究[J]. 轻工学报, 2024, 39(1): 97-102. doi: 10.12187/2024.01.012

引用本文: 李晓, 郭朋玮, 周茂忠, 等. 烟丝物理指标对其回弹特性的影响研究[J]. 轻工学报, 2024, 39(1): 97-102. doi: 10.12187/2024.01.012

烟丝物理指标对其回弹特性的影响研究

作者简介:李晓(1966-),女,河南省南阳市人,郑州轻工业大学教授,主要研究方向为卷烟加工技术。E-mail:519389150@qq.com

1. 郑州轻工业大学烟草科学与工程学院, 河南郑州 450001;
2. 红云红河烟草(集团)有限责任公司, 云南昆明 650231;
3. 河南中烟工业有限责任公司技术中心, 河南郑州 450000

收稿日期: 2023-04-26
录用日期: 2023-06-25

基金项目: 河南中烟工业有限责任公司重点项目(AW201911)中国烟草总公司标准项目(2020QB0012)

关键词:

摘要: 以5种牌号常规卷烟成品烟丝为研究对象,采用多重线性回归分析方法研究烟丝物理指标对其回弹特性的影响规律,并构建基于BP神经网络的烟丝回弹特性预测模型。结果表明:烟丝物理指标对烟丝回弹特性的影响程度从大到小依次为碎丝率>中丝率>长丝率>填充值>弹性>含水率,其中,中丝率、长丝率、弹性、含水率与烟丝回弹特性呈正相关关系,碎丝率、填充值与烟丝回弹特性呈负相关关系;所构建的BP神经网络预测模型,测试集预测值与真实值比对R²为0.965 7,总体模型精度达到98.10%,烟丝回弹特性预测值与实测值之间的差异较小,模型具有较高的预测准确性和可靠性,可用于烟丝回弹特性的精确估算。

English Abstract

Research on the influence of physical indicators of cut tobacco on its rebound characteristics

1. College of Tobacco Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou 450001, China;
2. Hongyun Honghe Tobacco (Group) Co., Ltd., Kunming 650231, China;
3. Technology Center, Henan Zhongyan Industry Co., Ltd., Zhengzhou 450000, China

Received Date: 2023-04-26
Accepted Date: 2023-06-25

Abstract: Using 5 grades of conventional cigarette finished tobacco as the research object, multiple linear regression analysis method was used to study the influence of physical indicators of cut tobacco on its rebound characteristics, and a prediction model for tobacco rebound characteristics based on BP neural network was constructed. The results showed that the degree of influence of physical indicators of cut tobacco on the rebound characteristics of tobacco was ranked from large to small as follows: broken tobacco rate>medium tobacco rate>long tobacco rate>filling value>elasticity>moisture content. Among them, medium tobacco rate, long tobacco rate, elasticity, and moisture content were positively correlated with the rebound characteristics of tobacco, while broken tobacco rate and filling value were negatively correlated with the rebound characteristics of tobacco. In the constructed BP neural network prediction model, the comparison between the predicted value of the test set and the true value R² was 0.965 7, the overall model accuracy reached 98.10% . The difference between the predicted and measured values of cut tobacco rebound characteristics was small, and the model had high prediction accuracy and reliability, which could be used for accurate estimation of cut tobacco rebound characteristics.