Corrosion rate prediction and influencing factors evaluation of low-alloy steels in marine atmosphere using machine learning approach
Luchun Yan, Yupeng Diao, Zhaoyang Lang, Kewei Gao
Abstract
values, 0.94 and 0.73 to the training set and testing set) to different low-alloy steel samples in several typical marine atmospheric environments. The results demonstrated that machine learning was efficient in corrosion behavior analysis, which usually involves a regression analysis of multiple factors.
Topics & Concepts
CorrosionRandom forestAlloyRegression analysisSet (abstract data type)Predictive modellingMetallurgyAtmosphere (unit)Materials scienceEmpirical modellingMachine learningComputer scienceSimulationMeteorologyPhysicsProgramming languageHydrogen embrittlement and corrosion behaviors in metalsCorrosion Behavior and InhibitionMachine Learning in Materials Science