[HTML][HTML] Interpretable machine learning for maximum corrosion depth and influence factor analysis
Y Song, Q Wang, X Zhang, L Dong, S Bai… - npj Materials …, 2023 - nature.com
We have employed interpretable methods to uncover the black-box model of the machine
learning (ML) for predicting the maximum pitting depth (dmax) of oil and gas pipelines …
learning (ML) for predicting the maximum pitting depth (dmax) of oil and gas pipelines …
Interpretable machine learning for maximum corrosion depth and influence factor analysis.
Y Song, Q Wang, X Zhang, L Dong… - NPJ Materials …, 2023 - search.ebscohost.com
We have employed interpretable methods to uncover the black-box model of the machine
learning (ML) for predicting the maximum pitting depth (dmax) of oil and gas pipelines …
learning (ML) for predicting the maximum pitting depth (dmax) of oil and gas pipelines …
Interpretable machine learning for maximum corrosion depth and influence factor analysis
Y Song, Q Wang, X Zhang, L Dong… - NPJ Materials …, 2023 - search.proquest.com
We have employed interpretable methods to uncover the black-box model of the machine
learning (ML) for predicting the maximum pitting depth (dmax) of oil and gas pipelines …
learning (ML) for predicting the maximum pitting depth (dmax) of oil and gas pipelines …