Application of Genetic Neural Network in Coal Quality Analysis with Near-infrared Spectroscopy

In view of the shortcomings of BP neural network,such as slow convergence,easily falling into local optimums,the paper put forward a method of establishment of model of coal quality analysis with near-infrared spectroscopy based on GA-BP neural network and characteristics of global searching method of neural network.The principal component analysis(PCA) was used to get principal component values and to compress data.The results of traditional BP neural network model and GA-BP model were compared,and the result showed that the GA-BP neural network model could not only reduce error sum squares between the predictive value and truth value,but also improve the correlation coefficient,which improves precision of prediction and speed of analysis effectively.