Intellectualizing analysis and assessment of statistical data on field pipeline failures due to internal corrosion

Abstract

The paper presents some results of a study meant to create an expert system used to select a material design and method of internal corrosion protection for field pipelines at the design stage. The author has performed an intellectual analysis of operating statistical data on field pipeline failures. The first part of the paper describes the initial sample and the exploratory analysis performed. The second and the third parts describe the processes of creating and assessing a classifier based on the Random Forest algorithm. To assess the quality of the classifiers, the author has calculated the shares of correct answers in the algorithm (accuracy), precision and recall, as well as the F1-score. The author makes a conclusion about satisfactory values of quality metrics and outlines areas for further research.