Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
<p dir="ltr">Machine learning (ML) frameworks are transforming the development of corrosion inhibitors by enabling quantitative prediction of inhibition efficiency before synthesis. This work identifies the most reliable machine learning (ML) strategies for forecasting corrosion inhi...
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| Main Author: | Najam Us Sahar Riyaz (22927843) (author) |
|---|---|
| Other Authors: | Mazen Khaled (2979294) (author), Ali Alshami (18358488) (author), Ibnelwaleed A. Hussein (5535953) (author) |
| Published: |
2025
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| Subjects: | |
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