基于支持向量机的隧道空间光环境质量软测量  

Soft-sensing of Optical Environmental Quality in Tunnel Space Based on Support Vector Machine

作　　者：霍雅婷[1] 段中兴[1] 

机构地区：[1]西安建筑科技大学信息与控制工程学院,陕西西安710055

出　　处：《现代电子技术》2011年第8期167-169,173,共4页Modern Electronics Technique

摘　　要：软测量技术的关键是建立优良的软测量数学模型,最小二乘支持向量机(LS-SVM)以其优良的泛化特性而被应用到软测量建模中。在分析隧道空间光环境质量影响因素的基础上,提出基于最小二乘支持向量机建模的隧道空间光环境质量软测量方法,给出了相应的系统结构和算法。仿真结果表明,基于LS-SVM的软测量能够较好地对隧道空间光环境质量做出预测,是软测量建模的一种有效方法。The key technology of soft-sensing is to establish an excellent soft-measurement mathematical model.Least squares support vector machine（LS-SVM） for its good generalization has been applied to soft sensor modeling.On the basis of analyzing the influencing factors of optical environment quality in the tunnel space,a soft-measurement method of optical environment quality in tunnel space is proposed based on the modeling of least squares support vector machine.The corresponding system architecture and algorithm are given in this paper.Simulation results show that LS-SVM-based soft sensor can predict the optical environment quality in tunnel space,and is an effective method of soft sensor modeling.

关 键 词：光环境质量 软测量 最小二乘支持向量机 隧道空间 

分 类 号：TN911-34[电子电信—通信与信息系统]