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基于支持向量机的软测量建模方法
引用本文:马勇,黄德先,金以慧.基于支持向量机的软测量建模方法[J].信息与控制,2004,33(4):417-421.
作者姓名:马勇  黄德先  金以慧
作者单位:清华大学自动化系,北京,100084
摘    要:提出了一种基于支持向量机的软测量方法,并建立了青霉素发酵过程中菌丝浓度的软测量模型,通过实验分析了参数调整和核函数选择对支持向量机建模的影响.利用现场数据建立各种软测量模型可以发现,与其他软测量方法相比,支持向量机方法在理论上优于人工神经网络等其他建模方法.

关 键 词:支持向量机  发酵  软测量  神经网络  部分最tb-乘
文章编号:1002-0411(2004)04-0417-05

Soft-sensor Modeling Method Based on Support Vector Machine
MA Yong,HUANG De xian,JIN Yi hui.Soft-sensor Modeling Method Based on Support Vector Machine[J].Information and Control,2004,33(4):417-421.
Authors:MA Yong  HUANG De xian  JIN Yi hui
Abstract:A soft sensor method based on support vector machine is presented, and a soft sensor model for biomass estimation in penicillium fermentation process is developed by this method.The effects of parameter adjusting and selection of kernel functions on model quality are analyzed by simulation experiments.With data collected from real plant,models based on some other technologies are also presented.Experiments show that support vector machine method is superior to traditional modeling methods in theory.
Keywords:support vector machine  fermentation  soft-sensor  neural networks  partial least squares
本文献已被 CNKI 维普 万方数据 等数据库收录!
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