PLS algorithm for radial basis function networks

被引：0

作者：

Wang, Y ^{[1
]}

Rong, G ^{[1
]}

Wang, SQ ^{[1
]}

机构：

[1] Zhejiang Univ, Natl Key Lab Ind Control Ind, Hangzhou 310027, Peoples R China

来源：

PROCEEDINGS OF THE 37TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-4 | 1998年

关键词：

radial basis function network; partial least squares (PLS) algorithm; nonlinear modeling; product quality predictor;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The PLS (partial least squares) algorithm is introduced into the radial basis function (RBF) networks to construct MIMO nonlinear models. The PLS algorithm projects the correlated basis functions and the outputs down to a number of principal factors to construct parsimonious models. Example of nonlinear modeling is used to demonstrate better generalization and noise tolerable performance of the proposed algorithm than the full RBF network models. Finally, it is used as a product quality predictor for industrial distillation columns.

引用

页码：4748 / 4753

页数：6

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