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...
محفوظ في:
| المؤلف الرئيسي: | Najam Us Sahar Riyaz (22927843) (author) |
|---|---|
| مؤلفون آخرون: | Mazen Khaled (2979294) (author), Ali Alshami (18358488) (author), Ibnelwaleed A. Hussein (5535953) (author) |
| منشور في: |
2025
|
| الموضوعات: | |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Studies on Natural Extracts as Inhibitors of Mild Steel Corrosion in 1M HC1 Solution
حسب: Shanableh, Alaa
منشور في: (2011) -
Innovative dual-functional, green and biodegradable dicarboxylated inulin as scale and corrosion inhibitors for sustainable oil and gas operations
حسب: Showkat Ali Ganie (20602120)
منشور في: (2025) -
Enhancing the corrosion resistance of reinforcing steel under aggressive operational conditions using behentrimonium chloride
حسب: A. Bahgat Radwan (9631720)
منشور في: (2019) -
Corrosion Inhibition of Mild Steel using Potato Peel Extract in 2M HCl Solution
حسب: Ibrahim, Taleb
منشور في: (2011) -
Corrosion Inhibition of Mild Steel using Fig Leaves Extract in Hydrochloric Acid Solution
حسب: Ibrahim, Taleb
منشور في: (2011)