| 基于支持向量机的软测量建模方法的应用 |
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| 引用本文： | 崔永超,张湜,王永华.基于支持向量机的软测量建模方法的应用[J].陶瓷科学与艺术,2007(3). |
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| 作者姓名： | 崔永超 张湜 王永华 |
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| 作者单位： | 南京工业大学自动化学院 江苏南京210009 |
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| 摘 要： | 利用基于最小二乘支持向量机(LS-SVM)的软测量建模方法,通过工业现场数据来对丁二烯精馏装置建立软测量模型.对于该软测量模型,支持向量机方法比BP神经网络方法具有更好的泛化能力.研究结果表明,基于最小二乘的支持向量机建模方法是一种有效的软测量建模方法.
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| 关 键 词： | 支持向量机 软测量 神经网络 |
Modeling method based on support vector machine and its application |
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| CUI Yong-chao,ZHANG Shi,WANG Yong-hua.Modeling method based on support vector machine and its application[J].Ceramics Science & Art,2007(3). |
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| Authors: | CUI Yong-chao ZHANG Shi WANG Yong-hua |
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| Abstract: | Using a soft-sensing modeling method on Least Square SVM(LS-SVM),the soft-sensing models of the butadiene distillation column were established by using the practical industry data.The method based on SVM has advantages better than BP neural network and other methods.The effective result indicates that the proposed method is powerful for modeling. |
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| Keywords: | support vector machine soft-sensing neural network |
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