BDA Models and Application for Recognizing the Headstreams of Mine Waterburst
BAYES discriminant analysis (BDA) method was used in the study of headstreams of prediction of minewater inrush and two BDA models for recognizing two-headstreams and multi-headstreams were constructed. Baesd on the principle of BDA theory and the classical headstream samples of different mines, the discriminant process and cross-validation method were introduced. 10 samples from a mine of HUA BEI Mine and 39 samples of JIAO ZUO Mine were used as data sources. Ca2+, Mg2+, Na+, K+, Cl-, HCO3-, SO42-, NO32-, F- and pH were selected as discriminant genes for two-headstreams BDA model and Na++K+, Ca2+, Mg2+, Cl-, SO42-, HCO3- were regarded as discriminant genes for multi-headstreams BDA model. Compared with the results of SQT method, ANN method and SVM method, the results show that the frame of BDA model was steady and high prediction accuracy can be obtained. BDA method and can be used in practical mine engineering.
Shengyi Li, Yingchun Liu, Rongbo Zhu, Hongguang Li, Wensi Ding
W. Wan and L. Jie, "BDA Models and Application for Recognizing the Headstreams of Mine Waterburst", Applied Mechanics and Materials, Vols. 34-35, pp. 1788-1793, 2010