Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/164607
Title: Classification method for failure modes of RC columns based on key characteristic parameters
Authors: Yu, Bo
Yu, Zecheng
Li, Qiming
Li, Bing
Keywords: Engineering::Civil engineering
Issue Date: 2022
Source: Yu, B., Yu, Z., Li, Q. & Li, B. (2022). Classification method for failure modes of RC columns based on key characteristic parameters. Structural Engineering and Mechanics, 84(1), 1-16. https://dx.doi.org/10.12989/sem.2022.84.1.001
Journal: Structural Engineering and Mechanics
Abstract: An efficient and accurate classification method for failure modes of reinforced concrete (RC) columns was proposed based on key characteristic parameters. The weight coefficients of seven characteristic parameters for failure modes of RC columns were determined first based on the support vector machine-recursive feature elimination. Then key characteristic parameters for classifying flexure, flexure-shear and shear failure modes of RC columns were selected respectively. Subsequently, a support vector machine with key characteristic parameters (SVM-K) was proposed to classify three types of failure modes of RC columns. The optimal parameters of SVM-K were determined by using the ten-fold cross-validation and the grid-search algorithm based on 270 sets of available experimental data. Results indicate that the proposed SVM-K has high overall accuracy, recall and precision (e.g., accuracy>95%, recall>90%, precision>90%), which means that the proposed SVM-K has superior performance for classification of failure modes of RC columns. Based on the selected key characteristic parameters for different types of failure modes of RC columns, the accuracy of SVM-K is improved and the decision function of SVM-K is simplified by reducing the dimensions and number of support vectors.
URI: https://hdl.handle.net/10356/164607
ISSN: 1225-4568
DOI: 10.12989/sem.2022.84.1.001
Schools: School of Civil and Environmental Engineering 
Rights: © 2022 Techno-Press. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:CEE Journal Articles

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