Research Article
Computational Intelligence-Based Structural Health Monitoring of Corroded and Eccentrically Loaded Reinforced Concrete Columns
Table 3
Selection of the best neuron based on R and MSE.
| S. no | Neuron | Values | Rank | Sum | MSE | R | MSE | R | Tr | Val | Te | Tr | Val | Te | Tr | Val | Te | Tr | Val | Te |
| 1 | 3 | 0.000345 | 0.001025 | 0.001274 | 0.9954 | 0.9751 | 0.9908 | 4 | 9 | 7 | 4 | 10 | 4 | 38 | 2 | 4 | 0.000447 | 0.001617 | 0.000697 | 0.9932 | 0.9936 | 0.9873 | 7 | 10 | 3 | 8 | 2 | 6 | 36 | 3 | 5 | 0.000294 | 0.000972 | 0.001290 | 0.9960 | 0.9850 | 0.9928 | 1 | 7 | 8 | 2 | 7 | 3 | 28 | 4 | 6 | 0.000508 | 0.000634 | 0.001315 | 0.9950 | 0.9924 | 0.9681 | 9 | 3 | 9 | 5 | 4 | 10 | 40 | 5 | 7 | 0.000470 | 0.002255 | 0.002673 | 0.9935 | 0.9855 | 0.9775 | 8 | 12 | 11 | 7 | 6 | 9 | 53 | 6 | 8 | 0.001054 | 0.000671 | 0.001150 | 0.9918 | 0.9798 | 0.9837 | 12 | 4 | 5 | 11 | 9 | 8 | 49 | 7 | 9 | 0.000353 | 0.000737 | 0.002149 | 0.9949 | 0.9916 | 0.9838 | 5 | 6 | 10 | 6 | 5 | 7 | 39 | 8 | 10 | 0.000365 | 0.000589 | 0.000749 | 0.9954 | 0.9927 | 0.9878 | 6 | 2 | 4 | 4 | 3 | 5 | 24 | 9 | 11 | 0.000329 | 0.000284 | 0.005258 | 0.9960 | 0.9951 | 0.9513 | 2 | 1 | 13 | 2 | 1 | 11 | 30 | 10 | 12 | 0.000822 | 0.001790 | 0.004870 | 0.9929 | 0.8821 | 0.9464 | 11 | 11 | 12 | 9 | 13 | 12 | 68 | 11 | 13 | 0.000365 | 0.000691 | 0.000478 | 0.9958 | 0.9702 | 0.9935 | 6 | 5 | 2 | 3 | 12 | 2 | 30 | 12 | 14 | 0.000332 | 0.001020 | 0.001260 | 0.9964 | 0.9747 | 0.9201 | 3 | 8 | 6 | 1 | 11 | 13 | 42 | 13 | 15 | 0.000534 | 0.002312 | 0.000444 | 0.9926 | 0.9840 | 0.9951 | 10 | 13 | 1 | 10 | 8 | 1 | 43 |
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Tr = training, Val = validation, and Te = testing.
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