Parallel based support vector regression for empirical modeling of nonlinear chemical process systems
In this paper, a support vector regression (SVR) using radial basis function (RBF) kernel is proposed using an integrated parallel linear-and-nonlinear model framework for empirical modeling of nonlinear chemical process systems. Utilizing linear orthonormal basis filters (OBF) model to represent th...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Penerbit Universiti Kebangsaan Malaysia,
2018-03.
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| Online Access: | Get fulltext |