Application of support vector machine with firefly algorithm for investigation of the factors affecting the shear strength of angle shear connectors

被引:255
作者
Chahnasir, E. Sadeghipour [1 ]
Zandi, Y. [2 ]
Shariati, M. [3 ,4 ]
Dehghani, E. [5 ]
Toghroli, A. [4 ]
Mohamed, E. Tonnizam [6 ]
Shariati, A. [7 ]
Safa, M. [4 ]
Wakil, K. [8 ,9 ]
Khorami, M. [10 ]
机构
[1] Islamic Azad Univ, Dept Civil Engn, Qeshm Int Branch, Qeshm, Iran
[2] Islamic Azad Univ, Dept Civil Engn, Tabriz Branch, Tabriz, Iran
[3] Univ Tabriz, Fac Civil Engn, Tabriz, Iran
[4] Univ Malaya, Fac Engn, Dept Civil Engn, Kuala Lumpur, Malaysia
[5] Univ Qom, Dept Civil Engn, Qom, Iran
[6] Univ Teknol Malaysia, Fac Civil Engn, Ctr Trop Geoengn GEOTROPIK, Johor Baharu, Malaysia
[7] Islamic Azad Univ, Dept Civil Engn, South Tehran Branch, Tehran, Iran
[8] Sulaimani Polytech Univ, Tech Coll Informat, Informat Technol Dept, Sulaymaniyah, Iraq
[9] Univ Human Dev, Sulaimani, Iraq
[10] Univ Tecnol Equinoccial, Fac Arquitectura & Urbanismo, Calle Rumipamba S-N & Bourgeois, Quito, Ecuador
关键词
C-shaped shear connector; channel; estimation; prediction; support vector machine; firefly algorithm; STEEL RINGS; COMPOSITE BEAMS; CHANNEL; PERFORMANCE; BEHAVIOR; PREDICTION; DUCTILITY; SYSTEM; ANFIS; MODEL;
D O I
10.12989/sss.2018.22.4.413
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The factors affecting the shear strength of the angle shear connectors in the steel-concrete composite beams can play an important role to estimate the efficacy of a composite beam. Therefore, the current study has aimed to verify the output of shear capacity of angle shear connector according to the input provided by Support Vector Machine (SVM) coupled with Firefly Algorithm (H A). SVM parameters have been optimized through the use of FFA, while genetic programming (GP) and artificial neural networks (ANN) have been applied to estimate and predict the SVM-FFA models' results. Following these results, GP and ANN have been applied to develop the prediction accuracy and generalization capability of SVM-FFA Therefore, SVM-FFA could be performed as a novel model with predictive strategy in the shear capacity estimation of angle shear connectors. According to the results, the Firefly algorithm has produced a generalized performance and be learnt faster than the conventional learning algorithms.
引用
收藏
页码:413 / 424
页数:12
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