Prediction of R in Sinter Process based on Grey Neural Network Algebra

A grey neural network model was proposed on the basis of the models. The fluctuation of data sequence is weakened by the grey theory and the neural network is capable of processing non-linear adaptable information, and the GNN is a combination of those advantages. The results reveal, the alkalinity of sinter can be accurately predicted through this model by reference to small sample and information. It was concluded that the GNN model is effective with the advantages of high precision, less requirement of samples and comparatively simple calculation.