Research Article
An Artificial Intelligence Approach for Groutability Estimation Based on Autotuning Support Vector Machine
| Case | IF1 | IF2 | IF3 | IF4 | IF5 | IF6 | IF7 | Desired output |
| 1 | 2.987 | 4.443 | 0.373 | 10.330 | 16.935 | 456.023 | 4.650 | −1 | 2 | 1.798 | 2.446 | 0.378 | 8.754 | 20.579 | 563.269 | 4.650 | −1 | 3 | 6.128 | 11.058 | 0.367 | 15.614 | 13.707 | 205.009 | 4.000 | −1 | | | | | | | | | | 238 | 9.015 | 18.046 | 0.360 | 23.957 | 16.935 | 228.777 | 4.000 | −1 | 239 | 20.985 | 31.026 | 0.355 | 14.409 | 11.677 | 126.748 | 4.000 | +1 | 240 | 11.986 | 27.032 | 0.360 | 19.878 | 14.125 | 145.878 | 4.000 | +1 |
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Note: output = −1: unsuccessful grouting. Output = +1: successful grouting.
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