Data-driven Corrosion Prediction
Data-Driven Corrosion Prediction is a computational modeling approach that distinguishes itself by leveraging empirical data and statistical learning techniques to forecast corrosion behavior without relying primarily on mechanistic or theoretical assumptions.
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5K
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445
Authors
191
Institutions
Publications per year
2017–2026
115
Parents
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Predicting the Performance of Organic Corrosion Inhibitors
David A. Winkler · Metals · 2017 · 111 citations · Full text
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University of Science and Technology Beijing
Beijing, China
13 h-index
71 publications
3.9K citations
Southwest Petroleum University
Chengdu, China
9 h-index
25 publications
1.4K citations

Southeast University
Nanjing, China
8 h-index
12 publications
663 citations
Xi'an University of Architecture and Technology
Xi'an, China
5 h-index
14 publications
969 citations
Memorial University of Newfoundland
St. John's, Canada
4 h-index
6 publications
236 citations

Beijing University of Chemical Technology
Beijing, China
3 h-index
11 publications
300 citations

China University of Petroleum, Beijing
Beijing, China
3 h-index
14 publications
560 citations

Lanzhou University of Technology
Lanzhou, China
3 h-index
3 publications
110 citations
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11 publications · 496 citations
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