﻿ 基于PLS回归的单箱消耗影响因素分析—来自红河卷烟厂卷包过程中的烟丝消耗控制数据

# 基于PLS回归的单箱消耗影响因素分析—来自红河卷烟厂卷包过程中的烟丝消耗控制数据The Analysis of Influence Factors of Single Box Consumption Based on the PLS Regression—From the Data of Tobacco Consumption Control in Honghe Cigarette Factory

Abstract: On the basis of some conditions for the application of partial least squares regression analysis and multivariate linear regression analysis in this paper, we can conclude that partial least squares regression (PLS) can effectively improve multicollinearity of variables. When the sample size is less than the number of variables, it also can be used to do regression modeling. Then, from 12 groups of sample data of Tobacco consumption control in Honghe Cigarette Factory, we have analyzed and compared the results of partial least squares regression modeling and multivariate linear regression modeling in the paper. It has shown that the significant factors affecting the single box consumption are single case of Wasting, single case of Running, single case of Packet rejection and single case of Short excluded volume. Therefore, the work of the cigarette factory in the process of reducing the cost should be firstly controlling these four single box loss indicators, so that we will achieve the immediate results.

[1] 贺万华, 曹兴洪, 等 (2007) 卷烟制丝和卷制过程中主要质量指标与消耗指标的关系及评价方法. 中国烟草学报, 5, 17-22.

[2] 汪涛, 张琦 (2011) 利用主成分分析和正交试验解决卷烟加工中的原料消耗问题. 黑龙江科技信息, 5, 50.

[3] 何晓群, 刘文卿 (2007) 应用回归分析. 中国人民大学出版社, 北京.

[4] Wold, H. (1975) Soft modelling by latent variables: The non-linear iterative partial least squares (NIPALS) approach. Perspectives in proba-bility and statistics. Papers in Honour of M. S. Bartlett. Academic Press, London, 117-142.

[5] 王惠文 (1999) 偏最小二乘回归方法及应用. 国防工业出版社, 北京.

Top