Journal
NPJ MATERIALS DEGRADATION
Volume 6, Issue 1, Pages -Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41529-022-00218-4
Keywords
-
Categories
Ask authors/readers for more resources
This work provides a data-oriented overview of machine learning applied to predicting electrochemical corrosion, creating a database to guide experts and developers and discussing potential research gaps and recommendations.
This work provides a data-oriented overview of the rapidly growing research field covering machine learning (ML) applied to predicting electrochemical corrosion. Our main aim was to determine which ML models have been applied and how well they performed depending on the corrosion topic considered. From an extensive review of corrosion articles presenting comparable performance metrics, a 'Machine learning for corrosion database' was created, guiding corrosion experts and model developers in their applications of ML to corrosion. Potential research gaps and recommendations are discussed, and a broad perspective for future research paths is provided.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available