Application of the random forest algorithm to predict the corrosion losses of carbon steel over the first year of exposure in various regions of the world

Abstract

The random forest (RF) algorithm was used to develop two models for predicting the first-year corrosion losses (C ₁) of carbon steel in open air in various regions of the world. The first RF model built using combined databases of international programmes ISO CORRAG, MICAT and ECE/UN and tests conducted in Russia is intended for estimation of C ₁ in various types of atmospheres in various regions of the world. The second RF model enables the prediction of C ₁ in continental areas of the world. The accuracy of C ₁ predictions by the two RF and two dose–response functions, i.e. the function presented in ISO 9223 standard and the new version for a non-marine atmosphere, was compared. The reliability of the two RF models was shown to be significantly higher than that of the dose–response functions with exception of the predictions for corrosion losses of carbon steel in regions of Russia with a cold climate.