NDLI: Cultural Particle Swarm Optimization Neural Network and Its Application in Soft-Sensing Modeling

Content Provider	IEEE Xplore Digital Library
Author	Guochu Chen
Copyright Year	2009
Abstract	Combining particle swarm optimization algorithm (PSO) with cultural algorithm (CA), a new cultural particle swarm optimization algorithm (CPSO) is proposed by this paper. Then, Both CPSO and PSO are used to resolve the optimization problems of five widely used test functions, and the results show that CPSO has better optimization performance than PSO. Next, CPSO is applied to train artificial neural network (NN) to construct a neural network based on cultural particle swarm optimization algorithm (CPSONN). Finally, CPSONN is applied in soft-sensing modeling of acrylonitrile yield and simulation results show that the method proposed by this paper is feasible and effective in soft-sensing modeling of acrylonitrile yield.
Starting Page	229
Ending Page	235
File Size	911169
Page Count	7
File Format	PDF
ISBN	9780769537368
DOI	10.1109/ICNC.2009.102
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Chemical industry Humans Artificial neural networks acrylonitrile Chemical processes Cultural differences Particle swarm optimization Biological neural networks cultural algorithm Neural networks optimization Computer networks model Global communication particle swarm optimization algorithm
Content Type	Text
Resource Type	Article

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