Dynamic neural networks partial least squares (DNNPLS) identification of multivariable processes

@article{Adebiyi2003DynamicNN,
  title={Dynamic neural networks partial least squares (DNNPLS) identification of multivariable processes},
  author={Olufemi A. Adebiyi and Armando B. Corripio},
  journal={Computers & Chemical Engineering},
  year={2003},
  volume={27},
  pages={143-155}
}
This paper presents the dynamic neural networks partial least squares (DNNPLS) as a strategy for open-loop identification of multivariable chemical processes that circumvent some of the difficulties associated with multivariable process control. The DNNPLS is an extension of the neural networks’ partial least squares (NNPLS) developed by Qin and McAvoy (Comp. Chem. Eng. 20 (1992) 379). Here, a dynamic extension to the NNPLS algorithm is proposed in which the static neural network models in the… CONTINUE READING

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