基于PLS和SVM的纸张抗张强度建模比较  

Comparison of Paper Tensile Strength Prediction Models Based on PLS and SVM Methods

作　　者：陶劲松[1] 杨亚帆[1] 李远华[1] 

机构地区：[1]华南理工大学制浆造纸工程国家重点实验室,广东广州510640

出　　处：《华南理工大学学报（自然科学版）》2014年第7期132-137,共6页Journal of South China University of Technology(Natural Science Edition)

基　　金：国家自然科学基金资助项目(20906030);广东省科技计划项目高科技发展专项资金项目(20130119g);华南理工大学中央高校基本科研业务费专项资金资助项目(2014ZZ0055);华南理工大学制浆造纸工程国家重点实验室开放基金资助项目(201233);广东省科技计划重大科技专项(2010A080801002)

摘　　要：为解决纸张抗张强度预测模型实际相关性差、预测精度低的问题,基于某瓦楞纸厂生产线,通过机理分析筛选出影响抗张强度的生产变量,分别使用偏最小二乘法(PLS)和支持向量机法(SVM)对抗张强度建模,并通过相关性筛选后的简化模型对模型预测精度进行比较.结果表明,简化后的支持向量机模型更适合纸张抗张强度的现场预测,其均方根误差为321N/m,皮尔逊相关系数为0.909,预测速度快且模型精度较高.In order to solve the problems of poor practicality and low accuracy of the existing paper tensile strength prediction models , two prediction models respectively based on the partial least-squares （ PLS ） and the support vector machine （ SVM） are established for a corrugated paper mill by selecting parameters affecting paper tensile strength through mechanism analysis .Then, the two models are simplified by deleting parameters of low correlation with tensile strength , and the simplified models are compared in terms of prediction accuracy .The results show that the simplified SVM model , whose root mean square error and Pearson correlation coefficient are 321 N/m and 0.909 respectively , is a quick prediction model with a high accuracy , so it is more suitable for the on-line prediction of tensile strength .

关 键 词：纸张 抗张强度 建模 偏最小二乘法 支持向量机 

分 类 号：TQ619.4[化学工程—精细化工]