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

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.

作者: Xinggang Wu Mingzhe Yuan

作者单位: Key Laboratory of Industrial Informatics,Shenyang Institute of Automation,Chinese Academy of Science Key Laboratory of Industrial Informatics,the Shenyang Institute of Automation,Chinese Academy of Sci

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Information and Automation(2009年 IEEE信息与自动化国际学术会议)

会议地点: 珠海、澳门

会议语种:英文

页码: 1458-1461

在线出版日期: 2009-06-22（万方平台首次上网日期，不代表论文的发表时间）