Ensemble Machine Learning Models for Estimating Mechanical Curves of Concrete-Timber-Filled Steel Tubes

Kazemi, Farzin;Asgarkhani, Neda;Ghanbari-Ghazijahani, Tohid;Jankowski, Robert

Description

A set of 88 models of CTFSTs was provided in ABAQUS software, focusing on parameters of D, as steel tube diameter, D/t as the diameter-to-thickness ratio, and AT, AC, and AS for cross-sectional areas of timber, concrete, and steel, respectively. Moreover, fc, fy, and fT present the compressive strength of concrete, steel tube, and timber used in the CTFSTs. A full description of the inputs and outputs has been provided in the paper titled "Ensemble Machine Learning Models for Estimating Mechanical Curves of Concrete-Timber-Filled Steel Tubes" published in Engineering Applications of Artificial Intelligence. Please see the link below to find the paper.

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Mentions (0)

Metrics

Dataset Index

0.3

FAIR Score

65%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Mendeley Data

License

Creative Commons Attribution Non Commercial Share Alike 4.0 International

Assigned Domain

Subfield

Civil and Structural Engineering

Field

Engineering

Domain

Physical Sciences

Confidence Score

56%

Source

Scholar Data Model

Keywords

SteelMachine LearningMachine Learning AlgorithmMachine Learning TheoryGraphical User InterfaceMechanical PropertyReinforced ConcreteConcrete StructureComposite StructureConcrete Filled Steel TubeComposite ColumnTimberAutomated Machine Learning

Normalization Factors

FT

65.38

CTw

1.00

MTw

1.00