Research Article
A Machine Learning-Based Model for Predicting Atmospheric Corrosion Rate of Carbon Steel
Table 6
The variation range of input parameters.
| | Input parameters | L | ML | M | MH | H |
| | T (oC) (X1) | 17.400 | 21.469 | 25.538 | 29.169 | 32.800 | | RH (%) (X2) | 65.000 | 73.521 | 82.042 | 86.521 | 91.000 | | TOW (hrs) (X3) | 112.237 | 278.823 | 445.408 | 532.109 | 618.809 | | (mg/m2.day) (X4) | 5.641 | 9.263 | 12.886 | 19.370 | 25.854 | | SO2 (mg/m2.day) (X5) | 5.141 | 6.669 | 8.197 | 9.382 | 10.566 | | Rf (mm) (X6) | 10.700 | 111.890 | 213.079 | 688.390 | 1163.700 | | HoS (hrs) (X7) | 36.300 | 91.271 | 146.242 | 208.521 | 270.800 |
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