Random forest-based frame work for multi-distress prediction in CRCP: a feature importance approach
Abstract This study presents a data-driven framework to identify and evaluate key variables contributing to four major distresses in Continuously Reinforced Concrete Pavement (CRCP): longitudinal cracking, spalling, punchouts, and transverse cracking. A Random Forest regression approach was applied...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-08-01
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| Series: | Discover Civil Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44290-025-00302-z |
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