华南理工大学学报(自然科学版) ›› 2004, Vol. 32 ›› Issue (11): 51-54.

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基于 LS-SVM 的橡胶炭黑均匀度判定模型

康春江 汪国强 廖芹   

  1. 华南理工大学 数学科学学院‚广东 广州 510640
  • 收稿日期:2004-01-11 出版日期:2004-11-20 发布日期:2015-09-08
  • 通信作者: 康春江(1980-)‚男‚硕士生‚主要从事数理统计与信息管理的研究。 E-mail:chun-jiang@eyou.com
  • 作者简介:康春江(1980-)‚男‚硕士生‚主要从事数理统计与信息管理的研究。

Model to Determine Dispersed Homogeneous Degree of Carbon-black in Rubber Based on LS-SVM

Kang Chun-Jiang Wang Guo-Qiang Liao Qin   

  1. College of Mathematical Sciences‚South China Univ.of Tech.‚Guangzhou510640‚Guangdong‚China
  • Received:2004-01-11 Online:2004-11-20 Published:2015-09-08
  • Contact: 康春江(1980-)‚男‚硕士生‚主要从事数理统计与信息管理的研究。 E-mail:chun-jiang@eyou.com
  • About author:康春江(1980-)‚男‚硕士生‚主要从事数理统计与信息管理的研究。

摘要: 为了减少橡胶生产过程中的废品率‚需要间接、实时、准确地确定橡胶中炭黑的 分散均匀度.基于结构风险最小化原则的支持向量机(SVM)是一种新型的机器学习方法‚ 对于小样本决策具有良好的分类、推广能力.应用多元分类的最小二乘支持向量机建立了 橡胶炭黑分散均匀度六级判定模型‚并对实际数据进行判定‚平均错别率下降到3.6%.结 果表明该模型是可行的‚并能快速、准确地判定橡胶炭黑的分散均匀度.

关键词: 炭黑, 分散均匀度, 最小二乘支持向量机, 判定模型

Abstract: In order to decrease the rejection ratio in the rubber-producing process‚the dispersed homogeneous degree of carbon-black in rubber should be indirectly‚real time and accurately determined.Support Vector Machines based on the principle of structural risk minimization is a new machine learning method which is of excellent classification and generalization ability when being used in the small sample decision.In this paper‚a6-band determination model of dispersed homogeneous degree of carbon-black in rubber was established on the basis of mult-i class Least Squares Support Vector Machines‚and some practical data were determined by the model.The results show that the proposed model is practical and average rate of false determination reduce to3.6%‚and can determine the dispersed homogeneous degree of carbon-black in rubber quickly and correctly.

Key words: carbon-black, dispersed homogeneous degree, least squares support Vector Machine, discrimination model 

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