Research Article
Damage Identification of Urban Overpass Based on Hybrid Neurogenetic Algorithm Using Static and Dynamic Properties
Table 5
Testing cases for damage identification with multiple damage location.
| | Testing case | Damage section
(corresponding expected output) | Damage severity
(corresponding expected output) |
| | M1 | 1 and 3 (1-0-1-0) | 20%-30% (0.2-0-0.3-0) | | M2 | 1 and 3 (1-0-1-0) | 30%-35% (0.3-0-0.35-0) | | M3 | 1 and 3 (1-0-1-0) | 35%-35% (0.35-0-0.35-0) | | M4 | 1 and 3 (1-0-1-0) | 40%-20% (0.4-0-0.2-0) | | M5 | 2 and 4 (0-1-0-1) | 20%-30% (0-0.2-0-0.3) | | M6 | 2 and 4 (0-1-0-1) | 30%-35% (0-0.3-0-0.35) | | M7 | 2 and 4 (0-1-0-1) | 35%-35% (0-0.35-0-0.35) | | M8 | 2 and 4 (0-1-0-1) | 40%-20% (0-0.4-0-0.2) |
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