Application of VLBP neural network in energy dispersion x fluorescence quantitative analysis

Based on the basic BP neural network, the VLBP neural network is applied in energy dispersive X-ray fluorescence analysis. The basic BP and VLBP models were used to predict the same batch of measured lead-zinc samples, which proved the advantage of VLBP algorithm in quantitative analysis. The Zn element content of the lead-zinc ore sample was predicted by using the VLBP algorithm and compared with the chemical analysis value of the sample. The results show that the relative error between the predicted value and the chemical analysis value is less than 5%. The sample with the characteristic peak count exceeding the training range is selected for prediction. The relative error between the predicted value and the reference value is less than 5%, which can be used as a new and effective method in the field of quantitative analysis of geological sample elements. (authors)