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Data-driven modeling of punchouts in CRCP using GA-optimized gradient boosting machine | Synapse
March 3, 2026
Open Access
Data-driven modeling of punchouts in CRCP using GA-optimized gradient boosting machine
AA
Ali Alnaqbi
University of Sharjah
GA
Ghazi G. Al-Khateeb
Jordan University of Science and Technology
WZ
Waleed Zeiada
Mansoura University
Key Points
Punchouts in CRCP can be effectively modeled, enhancing predictive accuracy.
The study implements a gradient boosting machine optimized through a genetic algorithm.
Data-driven approaches provide valuable insights for construction projects.
These modeling techniques may lead to better decision-making in CRCP applications.
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Alnaqbi et al. (Thu,) studied this question.
synapsesocial.com/papers/69a75cf4c6e9836116a2643d
https://doi.org/https://doi.org/10.1007/s44444-026-00098-y