Predicting the Shear Strength of Reinforced Concrete Beams Using Support Vector Machine

A wide range of machine learning techniques have been successfully applied to model different civil engineering systems. The application of support vector machine (SVM) to predict the ultimate shear strengths of reinforced concrete (RC) beams with transverse reinforcements is investigated in this pa...

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Main Author: Cindrawaty Lesmana
Format: Article
Language:English
Published: Universitas Kristen Maranatha 2019-03-01
Series:Jurnal Teknik Sipil
Subjects:
Online Access:https://journal.maranatha.edu/index.php/jts/article/view/1257
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author Cindrawaty Lesmana
author_facet Cindrawaty Lesmana
author_sort Cindrawaty Lesmana
collection DOAJ
description A wide range of machine learning techniques have been successfully applied to model different civil engineering systems. The application of support vector machine (SVM) to predict the ultimate shear strengths of reinforced concrete (RC) beams with transverse reinforcements is investigated in this paper. An SVM model is built trained and tested using the available test data of 175 RC beams collected from the technical literature. The data used in the SVM model are arranged in a format of nine input parameters that cover the cylinder concrete compressive strength, yield strength of the longitudinal and transverse reinforcing bars, the shear-span-to-effective-depth ratio, the span-toeffective- depth ratio, beam’s cross-sectional dimensions, and the longitudinal and transverse reinforcement ratios. The relative performance of the SVMs shear strength predicted results were also compared to ACI building code and artificial neural network (ANNs) on the same data sets. Furthermore, the SVM shows good performance and it is proved to be competitive with ANN model and empirical solution from ACI-05.
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spelling doaj.art-566ecd775e5a445b908d42bcff2ce82b2023-06-02T09:53:47ZengUniversitas Kristen MaranathaJurnal Teknik Sipil1411-93312549-72192019-03-0122749510.28932/jts.v2i2.1257908Predicting the Shear Strength of Reinforced Concrete Beams Using Support Vector MachineCindrawaty LesmanaA wide range of machine learning techniques have been successfully applied to model different civil engineering systems. The application of support vector machine (SVM) to predict the ultimate shear strengths of reinforced concrete (RC) beams with transverse reinforcements is investigated in this paper. An SVM model is built trained and tested using the available test data of 175 RC beams collected from the technical literature. The data used in the SVM model are arranged in a format of nine input parameters that cover the cylinder concrete compressive strength, yield strength of the longitudinal and transverse reinforcing bars, the shear-span-to-effective-depth ratio, the span-toeffective- depth ratio, beam’s cross-sectional dimensions, and the longitudinal and transverse reinforcement ratios. The relative performance of the SVMs shear strength predicted results were also compared to ACI building code and artificial neural network (ANNs) on the same data sets. Furthermore, the SVM shows good performance and it is proved to be competitive with ANN model and empirical solution from ACI-05.https://journal.maranatha.edu/index.php/jts/article/view/1257support vector machine, shear strength, reinforced concrete.
spellingShingle Cindrawaty Lesmana
Predicting the Shear Strength of Reinforced Concrete Beams Using Support Vector Machine
Jurnal Teknik Sipil
support vector machine, shear strength, reinforced concrete.
title Predicting the Shear Strength of Reinforced Concrete Beams Using Support Vector Machine
title_full Predicting the Shear Strength of Reinforced Concrete Beams Using Support Vector Machine
title_fullStr Predicting the Shear Strength of Reinforced Concrete Beams Using Support Vector Machine
title_full_unstemmed Predicting the Shear Strength of Reinforced Concrete Beams Using Support Vector Machine
title_short Predicting the Shear Strength of Reinforced Concrete Beams Using Support Vector Machine
title_sort predicting the shear strength of reinforced concrete beams using support vector machine
topic support vector machine, shear strength, reinforced concrete.
url https://journal.maranatha.edu/index.php/jts/article/view/1257
work_keys_str_mv AT cindrawatylesmana predictingtheshearstrengthofreinforcedconcretebeamsusingsupportvectormachine