DocumentCode :
2974163
Title :
Soft-sensor modeling of product particle size in ball milling circuits based on fuzzy neural networks with particle swarm optimization
Author :
Wu, Xinggang ; Yuan, Mingzhe
Author_Institution :
Key Lab. of Ind. Inf., Chinese Acad. of Sci., Shenyang, China
fYear :
2009
fDate :
22-24 June 2009
Firstpage :
1458
Lastpage :
1461
Abstract :
By combining particle swarm optimization algorithm (PSO) with fuzzy neural networks (FNN), a PSO fuzzy neural networks (PSO-FNN) was proposed. Then PSO-FNN was applied in soft-sensor modeling of product particle size in ball milling circuits. The new method assumed that FNN was used to construct the soft-sensor modeling of product particle size while PSO was employed to optimize parameters of FNN. Experiment results show that the model based on PSO-FNN has higher precision and better performance than the model based on BPNN.
Keywords :
ball milling; fuzzy neural nets; particle size; particle swarm optimisation; production engineering computing; sizing (materials processing); FNN; PSO; ball milling circuits; fuzzy neural network; particle swarm optimization; product particle size; soft-sensor modeling; Automation; Ball milling; Circuits; Fuzzy neural networks; Informatics; Optimization methods; Parameter estimation; Particle measurements; Particle swarm optimization; Size measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Automation, 2009. ICIA '09. International Conference on
Conference_Location :
Zhuhai, Macau
Print_ISBN :
978-1-4244-3607-1
Electronic_ISBN :
978-1-4244-3608-8
Type :
conf
DOI :
10.1109/ICINFA.2009.5205146
Filename :
5205146
Link To Document :
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