A new prediction model for the load capacity of castellated steel beams

被引:92
|
作者
Gandomi, Amir Hossein [1 ]
Tabatabaei, Seyed Morteza [2 ]
Moradian, Mohammad Hossein [3 ]
Radfar, Ata [4 ]
Alavi, Amir Hossein [5 ]
机构
[1] Tafresh Univ, Coll Civil Engn, Tafresh, Iran
[2] Inst Higher Educ Eqbal Lahoori, Dept Civil Engn, Mashhad, Iran
[3] Islamic Azad Univ, Dept Civil Engn, Sci & Res Branch, Tehran, Iran
[4] Ferdowsi Univ Mashhad, Dept Civil Engn, Mashhad, Iran
[5] Iran Univ Sci & Technol, Sch Civil Engn, Tehran, Iran
关键词
Castellated beam; Failure load; Gene expression programming; PROGRAMMING-BASED FORMULATION; DISTORTIONAL BUCKLING STRESS; WEB CRIPPLING STRENGTH; NEURAL-NETWORK; SHEAR;
D O I
10.1016/j.jcsr.2011.01.014
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In this study, a robust variant of genetic programming, namely gene expression programming (GEP), is utilized to build a prediction model for the load capacity of castellated steel beams. The proposed model relates the load capacity to the geometrical and mechanical properties of the castellated beams. The model is developed based on a reliable database obtained from the literature. To verify the applicability of the derived model, it is employed to estimate the load capacity of parts of the test results that were not included in the modeling process. The external validation of the model was further verified using several statistical criteria recommended by researchers. A multiple least squares regression analysis is performed to benchmark the GEP-based model. A sensitivity analysis is further carried out to determine the contributions of the parameters affecting the load capacity. The results indicate that the proposed model is effectively capable of evaluating the failure load of the castellated beams. The GEP-based design equation is remarkably straightforward and useful for pre-design applications. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1096 / 1105
页数:10
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