Soft sensor modeling of melt-index of High Pressure Low-Density Polyethylene

On the basis of analyzing the particle swarm optimization (PSO) algorithm and support vector machine (SVM), the PSO algorithm with chaos searching is applied to optimize the parameters of SVM, then the PSO-SVM model about a practical soft-sensor of melt-index of high pressure low-density polyethylen...

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Bibliographic Details
Main Authors: Bu Yan-ping, Yu Jin-shou
Format: Conference Proceeding
Language:chi ; eng
Subjects:
Analytical models
Chaos
Classification algorithms
melt-index
Particle swarm optimization
particle swarm optimization algorithm
Polyethylene
soft-sensor
support vector machine
Support vector machines
Training
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Summary:On the basis of analyzing the particle swarm optimization (PSO) algorithm and support vector machine (SVM), the PSO algorithm with chaos searching is applied to optimize the parameters of SVM, then the PSO-SVM model about a practical soft-sensor of melt-index of high pressure low-density polyethylene is constructed. The method takes advantages of the minimum structure risk of SVM and the quickly globally optimizing ability of PSO for soft sensor modeling. The simulation results demonstrate that the model has effective generalization performance, higher precision and engineering practicability.
ISSN:1948-9439
1948-9447
DOI:10.1109/CCDC.2008.4597637