| 一种改进的模糊PLS模型在软测量中的应用 |
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| 引用本文： | 张先林,于佐军. 一种改进的模糊PLS模型在软测量中的应用[J]. 控制工程, 2008, 0(Z2) |
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| 作者姓名： | 张先林 于佐军 |
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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 |
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| 摘 要： | 针对石油化工过程的特点,提出一种改进的模糊部分最小二乘的建模算法。该算法先用减法-模糊C均值聚类进行模糊结构辨识,然后用高斯核函数实现非线性PLS并且用其进行后件参数辨识,即得到多个子模型,再将各模型输出的数据进行隶属度加权求和得到最终的估计输出。最后,将该方法应用于航煤干点的估计,仿真结果表明该算法更有效,预测精度更高。
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| 关 键 词： | 模糊部分最小二乘 模糊C均值聚类 减法聚类 软测量 |
Application of a Modified Fuzzy Partial Least Squares Model in Soft Measurement |
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| ZHANG Xian-lin,YU Zuo-jun. Application of a Modified Fuzzy Partial Least Squares Model in Soft Measurement[J]. Control Engineering of China, 2008, 0(Z2) |
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| Authors: | ZHANG Xian-lin YU Zuo-jun |
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| Abstract: | A modified fuzzy partial least squares(PLS) model is presented for the characteristics of petrochemical process.In this method,the fuzzy structure is made by subtractive-fuzzy C-means clustering firstly,then the consequence parameter identification is obtained by a modified nonlinear PLS which is got by Gaussian kernel function,and some sub-models are gained.And then the degrees of membership are used for combing several sub-models to obtain the final result.Finally,this method is applied to the estimation of dry point of aviation kerosene oil,and the simulation results show the effectiveness and veracity. |
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| Keywords: | fuzzy partial least squares fuzzy C-means clustering subtractive clustering soft measurement |
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