An adaptive fuzzy combinatorial neural network model for predicting the composition of Pb-Zn agglomerate

Considering the characteristics of neural network modeling and empirical mechanism modeling, an adaptive fuzzy combinatorial model structure is proposed to effectively combine the two modeling methods together by use of the fuzzy classification. In the paper, the adaptive fuzzy combinatorial modeling is applied to the prediction of Pb-Zn agglomerate composition. Simulation results show that the proposed modeling is effective in the prediction of composition and meets the requirement of optimization computation for the blending process