CONSTRUCTION OF A NEURON NETWORK CLASSIFIER TO ANALYZE THE SITUATION AT A DRILLING SITE
Problems of: 1) selecting the mathematical means for solving the problem of recognition of situations that can appear while drilling and can lead to accidents, 2) developing and training a classifier based on an artificial neuron network have been considered. The analysis of basic mathematical methods applied for solving the image recognition problem has been done. A general structure of the neuron network classifier of the situations that can lead to accidents (PAS) has been proposed. Possibility and usefulness of solving the recognition problem for each individual situation that can lead to accidents have been shown; for that purpose, the problem of the neuron network classifier construction has been decomposed. A method for the recognition of the situations that can lead to accidents while commercial drilling oil and gas wells has been stated.