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- W2377256215 abstract "A high-precision on-line method of predicting melt index of propylene polymerization based on principal component analysis and particle swarm optimization is proposed to overcome the high correlation characteristics and high nonlinear characteristics in the propylene polymerization process.Principal component analysis,which obtains principal components with a small number of dynamic variables reflect the entire information,is employed to reduce the complexity of prediction model.Radial basis function neural network makes the foundation of the proposed model,and then particle swarm optimization algorithm is employed to improve its structure and parameters automatically.The validity of the proposed method is demonstrated through practical data in real factory.The detail comparison with the results of related report in the open literatures shows that the proposed model has a higher precision." @default.
- W2377256215 created "2016-06-24" @default.
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- W2377256215 date "2009-01-01" @default.
- W2377256215 modified "2023-09-24" @default.
- W2377256215 title "Melt Index Prediction Based on Particle Swarm Optimization" @default.
- W2377256215 hasPublicationYear "2009" @default.
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