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.