Journal of South China University of Technology (Natural Science Edition) ›› 2014, Vol. 42 ›› Issue (7): 132-137.doi: 10.3969/j.issn.1000-565X.2014.07.021

• Chemistry & Chemical Engineering • Previous Articles     Next Articles

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

Tao Jin-song Yang Ya-fan Li Yuan-hua   

  1. State Key Laboratory of Pulp and Paper Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2014-03-04 Online:2014-07-25 Published:2014-06-01
  • Contact: 陶劲松(1976-),男,博士,副研究员,主要从事制浆造纸工程计算机模拟与控制、节能与优化研究. E-mail:jstao@scut.edu.cn
  • About author:陶劲松(1976-),男,博士,副研究员,主要从事制浆造纸工程计算机模拟与控制、节能与优化研究.
  • Supported by:

    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)

Abstract:

In order to solve the problems of poor practicality and low accuracy of the existing paper tensile strengthprediction models,two prediction models respectively based on the partial least-squares ( PLS) and the supportvector machine ( SVM) are established for a corrugated paper mill by selecting parameters affecting paper tensilestrength through mechanism analysis.Then,the two models are simplified by deleting parameters of low correlationwith tensile strength,and the simplified models are compared in terms of prediction accuracy.The results show thatthe simplified SVM model,whose root mean square error and Pearson correlation coefficient are 321N/m and 0.909respectively,is a quick prediction model with a high accuracy,so it is more suitable for the on-line prediction oftensile strength.

Key words: paper, tensile strength, modeling, partial least squares, support vector machines