石油化工高等学校学报2013，Vol.26Issue(3)：74-78,5.DOI:10.3969/j.issn.1006-396X.2013.03.017
双核函数最小二乘支持向量机汽油干点软测量建模
Dual-Core Function Least Squares Support Vector Machine Soft Sensing Model of Gasoline Dry Point
摘要
Abstract
According to the function of mononuclear least squares support vector machine is easy to fall into local optimal value,the dual-core kernel function least squares support vector machine model method was proposed.This method uses Sigmoid kernel function and RBF kernel function which was linear weighted composing dual-core function,Removing the part of the smaller support vector sample method for improving the least squares support vector machine sparse characteristic,improving model operation speed,cross validation method was used to optimize the part of parameters.Finally the method was used to establish the gasoline dry point soft measurement model,compared with the standard support vector machine and the function of mononuclear least squares support vector machine.The results show that dual-core function least squares support vector machine model has higher calculation accuracy and better generalization ability.关键词
软测量/最小二乘支持向量机/双核函数/干点Key words
Soft sensing/ The least squares support vector machine/ Dual-core function/ Dry point分类
能源科技引用本文复制引用
赵连彬,苏成利..双核函数最小二乘支持向量机汽油干点软测量建模[J].石油化工高等学校学报,2013,26(3):74-78,5.基金项目
国家863计划项目资助(2007AA04Z162) （2007AA04Z162）
国家自然科学基金(61203021)资助 （61203021）
辽宁省科技攻关项目(2011216011) （2011216011）
辽宁省高校创新团队支持计划项目(2009T062、LT2010058)资助. （2009T062、LT2010058）
