Title :
Soft sensor modeling of melt-index of High Pressure Low-Density Polyethylene
Author :
Bu Yan-ping ; Yu Jin-shou
Author_Institution :
Res. Inst. of Autom., East China Univ. of Sci. & Technol., Shanghai
Abstract :
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.
Keywords :
chemical engineering computing; particle swarm optimisation; polymer melts; sensors; support vector machines; chaos searching; high pressure low-density polyethylene; melt-index; particle swarm optimization; soft sensor modeling; support vector machine; Algorithm design and analysis; Automation; Chaos; Lagrangian functions; Logistics; Optimization methods; Particle swarm optimization; Polyethylene; Support vector machines; chaos; melt-index; particle swarm optimization algorithm; soft-sensor; support vector machine;
Conference_Titel :
Control and Decision Conference, 2008. CCDC 2008. Chinese
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-1733-9
Electronic_ISBN :
978-1-4244-1734-6
DOI :
10.1109/CCDC.2008.4597637