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Lookup NU author(s): Dr Jie ZhangORCiD
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Starting from an equivalent presentation of projection to latent structures (PLS), a novel nonlinear PLS approach is presented where both nonlinear latent structures and nonlinear reconstruction are obtained straightforwardly through two consecutive steps. First, an radial basis functions (RBF) network is utilized to extract the latent structures through linear algebra methods without the need of nonlinear optimization. This is followed by two feed-forward networks (FFN) to reconstruct both the original predictor variables and response variables. The proposed algorithm exhibits fast convergence speed and its efficiency is assessed through both mathematical example and modelling of a pH neutralization process.
Author(s): Zhao SJ, Xu YM, Zhang J
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: Advances in Neural Networks: International Symposium on Neural Networks (ISNN 2004)
Year of Conference: 2004
Library holdings: Search Newcastle University Library for this item
Series Title: Lecture Notes in Computer Science