Prediction of the axial compression capacity of stub CFST columns using machine learning techniques
Khaled Megahed, Nabil S. Mahmoud, Saad Elden Mostafa Abd-Rabou
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Prediction of the axial compression capacity of stub CFST columns using machine learning techniques presents a particle swarm optimization approach for stub (electronics).
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Utility signals: depth 60/100, grounding 58/100, status medium.
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Research context
24
Citations
38
References
Tasks
Stub (electronics), Computer science, Support vector machine, Regression analysis, Robustness (evolution), Structural engineering, Engineering, Civil and Structural Engineering
Methods
Particle swarm optimization, Predictive modelling, Algorithm
Domains
Machine learning
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