Applications of Decision Tree and Random Forest as Tree-Based Machine Learning Techniques for Analyzing the Ultimate Strain of Spliced and Non-Spliced Reinforcement Bars

Applications of Decision Tree and Random Forest as Tree-Based Machine Learning Techniques for Analyzing the Ultimate Strain of Spliced and Non-Spliced Reinforcement Bars

The performance of both non-spliced and spliced steel bars significantly affects the overall performance of structural reinforced concrete elements. In this context, the mechanical properties of reinforcement bars (i.e., their ultimate strength and strain) should be determined in order to evaluate t...

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Bibliographic Details
Main Authors: Hamed Dabiri, Visar Farhangi, Mohammad Javad Moradi, Mehdi Zadehmohamad, Moses Karakouzian
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Applied Sciences
Subjects:
machine learning
reinforcement system
spliced bar
ultimate strain
Decision Tree
Random Forest
Online Access:https://www.mdpi.com/2076-3417/12/10/4851

Internet

https://www.mdpi.com/2076-3417/12/10/4851

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