| 基于模糊信息粒化软测量建模方法研究 |
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| 引用本文： | 王强,田学民.基于模糊信息粒化软测量建模方法研究[J].北京理工大学学报,2012,32(9):955-959. |
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| 作者姓名： | 王强 田学民 |
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| 作者单位： | 中国石油大学(华东)信息与控制工程学院,山东,青岛266580;东营职业学院工业工程系,山东,东营257091;中国石油大学(华东)信息与控制工程学院,山东,青岛266580 |
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| 基金项目： | 国家自然科学基金资助项目(51104175);山东省基金资助项目(ZR2011FM014) |
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| 摘 要： | 提出了一种模糊信息粒化方法和支持向量机相结合的软测量建模方法.利用模糊信息粒化方法对样本数据进行特征提取,降低样本的维数;利用提取的特征作为支持向量机的输入进行建模.用该方法建立柴油凝点的软测量模型,结果表明,该模型具有很好的预测精度和泛化性能,是一种有效的数据建模方法.
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| 关 键 词： | 软测量 模糊信息粒化 支持向量机 结构风险最小化 |
| 收稿时间： | 2012/2/25 0:00:00 |
Soft Sensing Based on Fuzzy Information Granulation |
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| WANG Qiang and TIAN Xue-min.Soft Sensing Based on Fuzzy Information Granulation[J].Journal of Beijing Institute of Technology(Natural Science Edition),2012,32(9):955-959. |
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| Authors: | WANG Qiang and TIAN Xue-min |
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| Institution: | College of Information and Control Engineering,China University of Petroleum, Qingdao, Shandong 266580, China;Department of Industry Engineering, Dongying Vocationnl College, Dongying, Shandong 257091, China;College of Information and Control Engineering,China University of Petroleum, Qingdao, Shandong 266580, China |
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| Abstract: | A kind of soft sensing model is proposed by combining methods of fuzzy information granulation (FIG) with support vector machine (SVM). The FIG has excellent performance of feature extraction and can reduce the dimension of the model sample in input data space. The extracted features are applied to SVM input for proceeding regressive modeling. Above measures are used to establish soft sensing model of diesel oil solidifying point. Results show that this model can get a good estimative accuracy and it is of wide extension as an effective method for data modeling. |
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| Keywords: | soft sensing fuzzy information granulation support vector machine structural risk minimization |
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