A hybrid machine learning approach in prediction and uncertainty quantification of ultimate compressive strength of RCFST columns

标题
A hybrid machine learning approach in prediction and uncertainty quantification of ultimate compressive strength of RCFST columns
作者
关键词
Concrete filled steel tube, Uncertainty quantification, Artificial neural networks, Particle swarm optimization, PANN, Design codes, Monte Carlo simulation
出版物
CONSTRUCTION AND BUILDING MATERIALS
Volume 302, Issue -, Pages 124208
出版商
Elsevier BV
发表日期
2021-07-17
DOI
10.1016/j.conbuildmat.2021.124208

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