Investigation of the Effectiveness of the Method for Recognizing Pre-Emergency Situations at Mining Facilities

Abstract

In previous reports, an analysis of the basic mathematical methods used to solve the pattern recognition problem was carried out. The inappropriateness of applying the Bayesian classification and cluster analysis to solve the problem of recognizing pre-emergency situations in the process of drilling a well is shown. As a mathematical apparatus for solving the problem of determining the current state of an object of research by a given set of features, a pattern recognition method based on an artificial neural network is selected. In this paper, an analysis is made of existing approaches to improving the quality of education aimed at improving the efficiency of its functioning. The results obtained in this paper will improve the quality of work of the previously developed modified algorithm for training the pre-emergency classifier based on the back propagation method, which differs from the classical one by the procedure for finding the global minimum of the error function, and its software implementation has been implemented. The work is an integral part of previously published developments presented in the materials of articles in 2-nd, 3-rd and 4-th International innovative mining symposiums (2017-2019).