Soft-sensor Modeling of Product Particle Size in Ball Milling Circuits Based on Fuzzy Neural Networks with Particle Swarm Optimization

被引：0

作者：

Wu, Xinggang ^{[1
]}

Yuan, Mingzhe ^{[1
]}

机构：

[1] Chinese Acad Sci, Shenyang Inst Automat, Key Lab Ind Informat, Shenyang, Peoples R China

来源：

ICIA: 2009 INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION, VOLS 1-3 | 2009年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：1433 / 1436

页数：4

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