Parallel based support vector regression for empirical modeling of nonlinear chemical process systems

• Main Authors: Zabiri, H., Marappagounder, R., Ramli, N.M.
• Format: Article
• Published: Penerbit Universiti Kebangsaan Malaysia 2018
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045654380&doi=10.17576%2fjsm-2018-4703-25&partnerID=40&md5=ab0ea71399a142639b56a8c597e3f7a6; http://eprints.utp.edu.my/21730/
• Institution: Universiti Teknologi Petronas

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...