Application of Fuzzy Neural Network in Predicting the Quality of Cupola Molten Iron
In this paper,a fuzzy neural network,with a five-storey structure back propagation network has been developed for predicting the quality of cupola molten iron.27 groups of the experimental samples were used to train the network and 4 groups are used to verify the network.The results show that for predicting the quality of molten iron with uncertainty and the multi-variable nonlinear object,to some extent,a fuzzy neural network model is better than conventional thermal analysis methods to eliminate the factitious limited on modeling and to improve the prediction accuracy and effective,and to be easy to deal with fuzzy information.It is shown that the method is feasible and has strong learning ability,generalization ability and adaptability.