Research Article
A Machine Learning-Based Model for Predicting Atmospheric Corrosion Rate of Carbon Steel
Table 1
Statistic properties of the experimental data.
| Input variable | T | RH | TOW | | SO2 | Rf | HoS | | (0C) | (%) | (hrs) | (mg/m2.day) | (mg/m2.day) | (mm) | (hrs) | (g/m2) | (X1) | (X2) | (X3) | (X4) | (X5) | (X6) | (X7) | (Output) |
| Min | 17.400 | 65.000 | 112.237 | 5.641 | 5.141 | 10.700 | 36.300 | 20.429 | Mean | 25.538 | 82.042 | 445.408 | 12.886 | 8.197 | 213.079 | 146.242 | 22.830 | Max | 32.800 | 91.000 | 618.809 | 25.854 | 10.566 | 1163.700 | 270.800 | 25.267 | SD | 4.424 | 6.921 | 136.214 | 6.220 | 1.684 | 306.325 | 64.788 | 1.076 | COV | 0.173 | 0.084 | 0.305 | 0.482 | 0.205 | 1.437 | 0.443 | 0.047 |
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