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中文摘要：
针对化工生产过程中软测量模型估计精度的问题，提出了一种基于多知识库挖掘理论的带监督的局部保持投影（SLPP）方法。该方法用SLPP算法对输入数据空间进行类与类之间的降维，得到不同的类别转换矩阵和不同的类别多知识库，最后融合支持向量机自适应地实现组合建模。仿真结果表明：该建模方法用于双酚A含量的软测量建模中，较传统多模型方法可以更加合理地加权得到子模型，提高了模型估计精度，具有更强的泛化能力。
英文摘要：
As for the problem of soft-sensor modeling estimation precision in chemical processing, a method of combination SVM soft-sensor modeling is proposed based on a theory of multiple knowledge bases, Supervised Locality Preserving Projection（SLPP）. The dimension of input data is reduced by SLPP between clusters, and then different transformed matrices and different multiple knowledge bases are gotten for every category. At last, a combination-model is constructed by support vector machine adaptively. Applied this method to a soft-sensor modeling of bisphenol A content, the simulation results
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