摘要
针对火电厂烟气含氧量的测量 ,提出了一种基于支持向量机的软测量建模方法 ,实验证明 ,该方法比较传统的氧量分析仪和RBF神经网络软测量均有着明显的优势 。
A soft sensor modeling via support vector machine(SVM) considering the problem of O_2 content in the power plant is presented.Experiments show that the SVM-based soft sensor has the evident advantages than both the traditional O_2 content instrument and the RBF-based soft sensor.And the SVM-based soft sensor is of important significance for the economical burning in the power plant.
出处
《测控技术》
CSCD
2004年第8期15-16,共2页
Measurement & Control Technology
基金
国家高技术研究发展计划 ( 863 )重点项目( 2 0 0 2AA412 0 10 )
关键词
烟气含氧量
软测量
径向基神经网络
支持向量机
O_2 content in flue gas
soft sensor
RBF neural networks
support vector machine(SVM)