Application of RBF network in the prediction of synthetic geophysical and geochemical methods to the lead-zinc polymetallic deposit

Many factors affect mineral deposit location, there is a very complicated nonlinear relationship that has been achieved only qualitative predictions between these factors and the deposit location. RBF neural network can achieve a high degree nonlinear mapping from input to output. In this paper, RBF neural network is used to predict lead-zinc mineral deposit in synthetic geophysical and geochemical exploration prediction in an area of Zhejiang province. The results show that the method has high accuracy, consistent with the high rate of the actual geological conditions, so that can be used as the prediction method of the concealed deposit.