Soft-sensor modeling of rectification of vinyl chloride based on improved PSO-RBF neural network

2012 ◽  
Author(s):  
Shuzhi Gao ◽  
Jie Sun ◽  
Xianwen Gao
Keyword(s):  
Neural Network ◽  
Vinyl Chloride ◽  
Rbf Neural Network ◽  
Soft Sensor ◽  
Sensor Modeling ◽  
Improved Pso

Algorithm Researching of RBF Neural Network Based on Improved PSO

2011 ◽  
Vol 179-180 ◽  
pp. 233-238 ◽  
Author(s):  
Hua Chen ◽  
Yi Ren Fan ◽  
Shao Gui Deng
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Rbf Neural Network ◽  
Particle Swarm ◽  
Parameter Vector ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Whole Space ◽  
Best Parameter ◽  
Improved Pso

In view of the defect of particle swarm optimization which easily gets into partial extremum, the paper put out an improved particle swarm optimization, and applies the algorithm to the selecting of parameter of RBF neural network basal function. It searches the best parameter vector in the whole space, according to coding means, iterative formula, adapted function which the paper puts forwards. The experiment proves that RBF neural network based on improved PSO has faster convergent speed, and higher error precision.

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