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

Title
A hybrid machine learning approach in prediction and uncertainty quantification of ultimate compressive strength of RCFST columns
Authors
Keywords
Concrete filled steel tube, Uncertainty quantification, Artificial neural networks, Particle swarm optimization, PANN, Design codes, Monte Carlo simulation
Journal
CONSTRUCTION AND BUILDING MATERIALS
Volume 302, Issue -, Pages 124208
Publisher
Elsevier BV
Online
2021-07-17
DOI
10.1016/j.conbuildmat.2021.124208

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