A model for predicting corrosion losses of carbon steel for the first year of exposure based on the random forest algorithm
https://doi.org/10.61852/2949-3412-2024-2-1-41-59
Abstract
Based on the random forest (RF) algorithm, two models have been obtained for predicting first-year corrosion losses (K1) of carbon steel in an open atmosphere in various regions of the world. The first RF_general model was obtained using the combined databases of the international ISO CORRAG, MICAT, ECE/UN programs and tests in Russia and is designed to assess K1 in various types of atmosphere in different regions of the world. The second RF_cont model allows you to predict K1 in the continental regions of the world. The accuracy of K1 predictions based on RF models and two dose-response functions was compared: the one presented in ISO 9223 standard and the new version developed by IPCE RAS for continental regions. It is shown that the reliability of both RF models is significantly better than the dose-response functions, with the exception of predictions of corrosion losses of steel in Russia with a cold climate.
About the Authors
M. A. Gavryushina
Frumkin Institute of Physical Chemistry and Electrochemistry of the Russian Academy of Sciences
Russian Federation
Russian Federation
31 Leninsky Prospekt, 4, Moscow, 119071
Yu. M. Panchenko
Frumkin Institute of Physical Chemistry and Electrochemistry of the Russian Academy of Sciences
Russian Federation
Russian Federation
31 Leninsky Prospekt, 4, Moscow, 119071
A. I. Marshakov
Frumkin Institute of Physical Chemistry and Electrochemistry of the Russian Academy of Sciences
Russian Federation
Russian Federation
31 Leninsky Prospekt, 4, Moscow, 119071
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Review
For citations:
Gavryushina M.A., Panchenko Yu.M., Marshakov A.I. A model for predicting corrosion losses of carbon steel for the first year of exposure based on the random forest algorithm. Title in english. 2024;(1):41-59. (In Russ.) https://doi.org/10.61852/2949-3412-2024-2-1-41-59
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