TY  - JOUR 
AU  - Tsiatas, George C.
AU  - Kotsiantis, Sotiris
AU  - Charalampakis, Aristotelis E.
PY  - 2022    
M3  - Original Research    
TI  - Predicting the Response of Laminated Composite Beams: A Comparison of Machine Learning Algorithms   
JO  - Frontiers in Built Environment  
UR  - https://www.frontiersin.org/article/10.3389/fbuil.2022.855112    
VL  - 8      
SN  - 2297-3362
N2  - A comparative study of machine learning regression algorithms for predicting the deflection of laminated composite beams is presented herein. The problem of the scarcity of experimental data is solved by ample numerically prepared data, which are necessary for the training, validation, and testing of the algorithms. To this end, the pertinent geometric and material properties of the beam are discretized appropriately, and a refined higher-order beam theory is employed for the accurate evaluation of the deflection in each case. The results indicate that the Extra-Trees algorithm performs best, demonstrating excellent predictive capabilities.
ER  -