Research on correlation of complex coal and rock seams based on improved back propagation neural network
Abstract：In order to improve the detection rate of correlation of complex coal and rock seams and solve the problem that the back propagate neural network ( BP neural network) is invalid when initial weight and threshold values of BP neural network are chosen impertinently, Genetic Algorithms (GA) ' s characteristic of getting whole optimization value was combined with BP' s character- istic of getting local precision value with gradient method. After getting an approximation of whole optimization value of weight and threshold values of BP neural network by GA, the approximation was used as the first parameter of BP neural network to train the BP neural network again. The trained BP neural network was used to correlation of complex coal seams. The accuracy of correlation of complex coal seams can be improved by the new method. In the paper, the sedimentary cycles with muhiscale characteristics based on wavelet transform of logging data was applied to correlation of complex coal seams. The practical experiment results shown that this method was useful and applicable for correlation of complex coal seams of Qianyingzi' s coal mine.
Keywords：Correlation of coal seamsglobal optimization valuegenetic algorithmsback propagation neural network
Publication Date：2012-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 9-12 )