节点文献
基于支持向量机的火电厂烟气含氧量软测量
SVM-Based Soft Sensor Applied to O2 Content in Flue Gas in the Power Plant
【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 ,对于实现火电厂经济燃烧有着重大的意义
【Abstract】 A soft sensor modeling via support vector machine(SVM) considering the problem of O2 content in the power plant is presented.Experiments show that the SVM-based soft sensor has the evident advantages than both the traditional O2 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.
【关键词】 烟气含氧量;
软测量;
径向基神经网络;
支持向量机;
【Key words】 O2 content in flue gas; soft sensor; RBF neural networks; support vector machine(SVM);
【Key words】 O2 content in flue gas; soft sensor; RBF neural networks; support vector machine(SVM);
【基金】 国家高技术研究发展计划 ( 863 )重点项目( 2 0 0 2AA412 0 10 )
- 【文献出处】 测控技术 ,Measurement & Control Technology , 编辑部邮箱 ,2004年08期
- 【分类号】TP274.4
- 【被引频次】48
- 【下载频次】347