Artificial intelligence as applied to classifying epoxy composites for aircraft

Abstract

The problem of classification of epoxy composites used for the manufacture of aircraft structures is solved by machine learning methods: neural network, reinforced trees and random forests. Classification metrics were obtained for each method used. Parameters such as precision, recall, F1 score and support were determined. The neural network classifier demonstrated the highest results. Boosted trees and random forests showed slightly lower results than the neural network method. At the same time, the classification metrics were high enough in each case. Therefore, machine learning methods effectively classify epoxy composites. The results obtained are in good agreement with the experimental ones. The prediction accuracy score obtained using each method was greater than 0.88