论文信息 - Nonlinear PLS modelling using radial basis functions

Nonlinear PLS modelling using radial basis functions

An approach to nonlinear partial least squares (PLS) modelling using radial basis function (RBF) neural networks to provide a nonlinear inner relationship is described, along with a technique (the hybrid BFGS algorithm) for training the networks. Results are given to show the performance with a number of different simulation examples, including a model of an industrial overheads condenser and reflux drum plant. Results confirm a significant improvement over linear PLS.

George W. Irwin | Gordon Lightbody | D.J.H. Wilson

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