Recognition of Rocks at Uranium Deposits by Using a Few Methods of Machine Learning

Uranium extraction in Kazakhstan is carried out using underground leaching method. Economic performance depends on the production process speed and accuracy of geophysical data interpretation. Data interpretation can be performed using learned systems, such as artificial neural network (ANN), Linear Discriminant Analysis Classifier (LDAC), Support Vector Classification (SVM), k-Nearest-Neighbor (k-NN) and etc. In the paper “adjacency cube” method for integration of results of few interpretation algorithms is proposed. Learning algorithm for the “adjacency cube” with low computational complexity was developed. The proposed method improves quality of recognition by 2-3 percent.