JAYA-GBRT model for predicting the shear strength of RC slender beams without stirrups

被引:1
作者
Tran, Viet-Lin [1 ,2 ]
Kim, Jin-Kook [1 ]
机构
[1] Seoul Natl Univ Sci & Technol, Dept Civil Engn, 232 Gongneung Ro, Seoul 01811, South Korea
[2] Vinh Univ, Dept Civil Engn, Vinh 461010, Vietnam
关键词
gradient boosting regression tree; graphic user interface; jaya algorithm; reinforced concrete slender beam; shear strength; web application; REINFORCED-CONCRETE BEAMS; AXIAL-COMPRESSION CAPACITY; FORMULATION; BEHAVIOR; MACHINE; PERFORMANCE;
D O I
10.12989/scs.2022.44.5.691
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Shear failure in reinforced concrete (RC) structures is very hazardous. This failure is rarely predicted and may occur without any prior signs. Accurate shear strength prediction of the RC members is challenging, and traditional methods have difficulty solving it. This study develops a JAYA-GBRT model based on the JAYA algorithm and the gradient boosting regression tree (GBRT) to predict the shear strength of RC slender beams without stirrups. Firstly, 484 tests are carefully collected and divided into training and test sets. Then, the hyperparameters of the GBRT model are determined using the JAYA algorithm and 10-fold cross-validation. The performance of the JAYA-GBRT model is compared with five well-known empirical models. The comparative results show that the JAYA-GBRT model (R-2= 0.982, RMSE = 9.466 kN, MAE = 6.299 kN, mu= 1.018, and Cov = 0.116) outperforms the other models. Moreover, the predictions of the JAYA-GBRT model are globally and locally explained using the Shapley Additive exPlanation (SHAP) method. The effective depth is determined as the most crucial parameter influencing the shear strength through the SHAP method. Finally, a Graphic User Interface (GUI) tool and a web application (WA) are developed to apply the JAYA-GBRT model for rapidly predicting the shear strength of RC slender beams without stirrups.
引用
收藏
页码:691 / 705
页数:14
相关论文
共 50 条
  • [31] Shear behavior of RC slender beams without stirrups by using precast U-shaped ECC permanent formwork
    Zhang, Rui
    Hu, Peng
    Zheng, Xiaohang
    Cai, Lianheng
    Guo, Rui
    Wei, Dingbang
    CONSTRUCTION AND BUILDING MATERIALS, 2020, 260
  • [32] Evolutionary Polynomial Regression Algorithm Enhanced with a Robust Formulation: Application to Shear Strength Prediction of RC Beams without Stirrups
    Marasco, Sebastiano
    Fiore, Alessandra
    Greco, Rita
    Cimellaro, Gian Paolo
    Marano, Giuseppe Carlo
    JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 2021, 35 (06)
  • [33] Reliability Assessment of Existing Equations Predicting the Shear Strength of Reinforced Concrete Beams without Stirrups
    Arslan, Guray
    Ibis, Aydogan
    Alacali, Sema Noyan
    TEKNIK DERGI, 2014, 25 (01): : 6601 - 6623
  • [34] Shear Strength of HVFA-SCC Beams without Stirrups
    Budi, Agus Setiya
    Safitri, Endah
    Sangadji, Senot
    Kristiawan, Stefanus Adi
    BUILDINGS, 2021, 11 (04)
  • [35] An experimental study on the shear strength of SFRC beams without stirrups
    Arslan G.
    Keskin R.S.O.
    Ulusoy S.
    1600, Polish Society of Theoretical and Allied Mechanics (55): : 1205 - 1217
  • [37] Shear strength of steel fiber reinforced concrete deep beams without stirrups
    Birincioglu, Mustafa I.
    Keskin, Riza S. O.
    Arslan, Guray
    ADVANCES IN CONCRETE CONSTRUCTION, 2022, 13 (01) : 1 - 10
  • [38] Behavior and shear strength of SFRC beams without stirrups: proposed model and parametric analyses
    Debella, Leticia Col
    de Sousa, Alex Micael Dantas
    de Resende, Thomas Lima
    Pieralisi, Ricardo
    STRUCTURES, 2024, 67
  • [39] BO-Stacking: A novel shear strength prediction model of RC beams with stirrups based on Bayesian Optimization and model stacking
    Shu, Jiangpeng
    Yu, Hongchuan
    Liu, Gaoyang
    Yang, Han
    Chen, Yanjuan
    Duan, Yuanfeng
    STRUCTURES, 2023, 58
  • [40] Shear strength prediction of HSC slender beams without web reinforcement
    Elsanadedy, H. M.
    Abbas, H.
    Al-Salloum, Y. A.
    Almusallam, T. H.
    MATERIALS AND STRUCTURES, 2016, 49 (09) : 3749 - 3772