LI Wei1, XU Hong-fei1, NI Yuan2. Soft-measurement for polymerization conversion rate of SBR based on kernel function PLS models[J]. 2012, 31(3): 143-146.
LI Wei1, XU Hong-fei1, NI Yuan2. Soft-measurement for polymerization conversion rate of SBR based on kernel function PLS models[J]. 2012, 31(3): 143-146. DOI: 10.13873/j.1000-97872012.03.005.
Aiming at the enterprise demand that polymerization conversion rate needs to be online high precision predicted for styrene butadiene rubber(SBR)
considering the complexity of actual working condition and the disadvantages of partial least squares(PLS)algorithm for its nonlinear processing power
PLS models with single or mixed kernel function are created separately and used to forecast the SBR polymerization conversion rate.The simulation results show that Kernel PLS models can all meet the enterprise requirements
which mean the ratio of polymerization conversion rate prediction absolute error greater than 1.5 is not more than 10 % of the total samples.Especially
the mixed Kernel PLS model shows more excellent properties because of its both local and global characteristics.
A novel multivariate regression approach based on kernel partial least squares with orthogonal signal correction [J] . Kyungpil Kim,Jong-Min Lee,In-Beum Lee. Chemometrics and Intelligent Laboratory Systems . 2005 (1)