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Abstract

Draw resistance and ventilation of cigarette are important indexes that affect the suction feeling, smoke and sensory quality of cigarette. In order to achieve the early prediction of draw resistance and ventilation of cigarette, the relevant factors were identified by analyzing the principle of draw resistance and ventilation, combined with a large number of data with different specifications and material characteristics. The prediction model of draw resistance and ventilation of cigarette was established by using multivariate adaptive regression splines (MARS) method. After verification, the normalized mean squared error (NMSE) of draw resistance prediction model was 0.276, and the average absolute error was 37.5 Pa; the NMSE of paper ventilation prediction model was 0.184, and the average absolute error was 0.91%; the NMSE of filter ventilation prediction model was 0.044, and the average absolute error was 1.27%. The results showed that the model could be applied to the prediction of cigarette draw resistance and ventilation in actual production, and provide a reference for cigarette materials matching in product design and production improvement.

Publication Date

3-28-2020

First Page

220

Last Page

224

DOI

10.13652/j.issn.1003-5788.2020.03.042

References

[1] DAVIS D L,NIELSEN M T.烟草:生产、化学和技术[M].国家烟草专卖局科技教育司,中国烟草科技信息中心,译.北京:化学工业出版社,2003:342.
[2] 中华人民共和国国家质量监督检验检疫总局.GBT 22838.15—2009 卷烟和滤棒物理性能的测定第15部分:卷烟通风的测定定义和测量原理[S].北京:中国标准出版社,2009:1-2.
[3] 孙东亮,王坤明,魏凤美,等.卷烟物理指标与吸阻统计关系研究[J].中国烟草科学,2008,29(4):42-45.
[4] 魏玉玲,徐金和,廖臻,等.卷烟材料多因素对卷烟通风率及过滤效率的影响[J].烟草科技,2008(11):10-14.
[5] 刘欢,王乐,胡少东,等.卷烟燃烧动态吸阻研究[J].食品与机械,2017,33(5):83-86.
[6] 高明奇,顾亮,李明哲,等.在线打孔参数对细支卷烟理化指标的影响[J].食品与机械,2017,33(11):200-203.
[7] 王乐,李斌,鲁端峰,等.不同抽吸状态下卷烟动态通风特征的数值模拟[J].烟草科技,2017,50(12):85-89.
[8] 王乐,崔晓梦,王兵,等.不同抽吸状态下卷烟内部气流流动特性的近似分析[J].烟草科技,2016,49(1):60-65.
[9] 王乐,游敏,崔晓梦,等.基于线性网络模型的卷烟吸阻及通风特征预测方法[J].烟草科技,2017,50(12):91-95.
[10] 范铁桢,倪克平,王涛.烟支内气流流量、吸阻与烟支长度的关系[J].烟草科技,2002(6):8-10.
[11] FRIEDMAN J H.Multivariate adaptive regression splin-es[J].The Annals of Statistics,1991,19(1):1-67.
[12] CORY LESMEISTER.精通机器学习:基于R[M].陈光欣,译.2版.北京:人民邮电出版社,2018:50-54.
[13] MAX K,KJELL J.应用预测建模[M].林荟,邱怡轩,马恩驰,等.译.北京:机械工业出版社,2016:103-108.
[14] 张秀敏,南卓铜,吴吉春,等.基于多元自适应回归样条的青藏高原温泉区域的冻土分布制图[J].冰川冻土,2011,33(5):1 088-1 097.
[15] 沈刘平,杨吉斌,曹铁勇,等.基于MARS的语音清晰度客观评价[J].数据采集与处理,2008(1):104-107.
[16] 吴喜之.应用回归及分类:基于R[M].北京:中国人民大学出版社,2016:4,38-40.欧盟评估一种甘油三酯脂肪酶的安全性

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