Quantum machine learning for corrosion resistance in stainless steel
This study evaluates the efficacy of quantum machine learning (QML) models in predicting stainless steel corrosion behaviour. Using two datasets, the quantum support vector classifier (QSVC) outperformed classical models, achieving accuracies of 95.46 % and 94.80 % for Dataset A and Dataset B, respe...
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| Main Authors: | Muhamad Akrom, Supriadi Rustad, Totok Sutojo, De Rosal Ignatius Moses Setiadi, Hermawan Kresno Dipojono, Ryo Maezono, Moses Solomon |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-09-01
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| Series: | Materials Today Quantum |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2950257824000131 |
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