NDLI: Multiobjective intelligence optimal operation of PET polymerization

Content Provider	IEEE Xplore Digital Library
Author	Liulin Cao Jing Wang Pei Jiang Qibing Jin
Copyright Year	2011
Description	Author affiliation: College of Information Science & Technology, Beijing University of Chemical Technology, North Sanhuan East Road 15, China (Liulin Cao; Jing Wang; Pei Jiang; Qibing Jin)
Abstract	A multiobjective intelligence optimal approach in polymerizing of PET with maximum yield and the best quality is proposed. The hybrid neural network based on B-spline and diagonal recursive neural network is used to model the PET process qualities, i.e. the Intrinsic Viscosity and Molecular Weight distribution. Then a hybrid NSGAII-PSO optimal algorithm with penalty functions is applied to solve the multiobjective optimal problem in order to get the best operation conditions. The simulation result indicates that the hybrid network model and model-based multiobjective optimal algorithm are effective.
Starting Page	336
Ending Page	340
File Size	1565330
Page Count	5
File Format	PDF
ISBN	9781612846989
e-ISBN	9781612847009
DOI	10.1109/WCICA.2011.5970754
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-21
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optimization Polymers Artificial neural networks Inductors Positron emission tomography Viscosity Predictive models NSGAII-PSO algorithm PET Multiobjective optimization hybrid neural network
Content Type	Text
Resource Type	Article

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