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Assessment of composite beam performance using GWO–ELM metaheuristic algorithm

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Abstract

Composite beams (CBs) include concrete slabs jointed to the steel parts by the shear connectors, which highly popular in modern structures such as high rise buildings and bridges. This study has investigated the structural behavior of simply supported CBs in which a concrete slab is jointed to a steel beam by headed stud shear connector. Determining the behavior of CB through empirical study except its costly process can also lead to inaccurate results. In this case, AI models as metaheuristic algorithms could be effectively used for solving difficult optimization problems, such as Genetic algorithm, Differential evolution, Firefly algorithm, Cuckoo search algorithm, etc. This research has used hybrid Extreme machine learning (ELM)–Grey wolf optimizer (GWO) to determine the general behavior of CB. Two models (ELM and GWO) and a hybrid algorithm (GWO–ELM) were developed and the results were compared through the regression parameters of determination coefficient (R2) and root mean square (RMSE). In testing phase, GWO with the RMSE value of 2.5057 and R2 value of 1.2510, ELM with the RMSE value of 4.52 and R2 value of 1.927, and GWO–ELM with the RMSE value of 0.9340 and R2 value of 0.9504 have demonstrated that the hybrid of GWO–ELM could indicate better performance compared to solo ELM and GWO models. In this case, GWO–ELM could determine the general behavior of CB faster, more accurate and with the least error percentages, so the hybrid of GWO–ELM is more reliable model than ELM and GWO in this study.

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Acknowledgements

The study presented herein was made possible by the Universiti Kebangsaan Malaysia Research Grant, GUP-2018-030.

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Authors and Affiliations

  1. Highway Bureau of Yulin City, Yulin, 710009, China

    Runqian Ma

  2. IIEES, Pasdaran Ave, Nourian St, Sholeh St, Tehran, Iran

    Misagh Karimzadeh

  3. Department of Civil, Environmental and Construction Engineering, Texas Tech University, Lubbock, TX, 79409, USA

    Aria Ghabussi

  4. Department of Civil Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran

    Yousef Zandi

  5. Department of Civil Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, UKM, 43600, Bangi, Selangor, Malaysia

    Shahrizan Baharom

  6. Department of Civil Engineering, College of Engineering, Prince Sattam bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia

    Abdellatif Selmi

  7. Ecole Nationale d’Ingénieurs deTunis (ENIT), Civil Engineering Laboratory, B.P. 37, Le belvédère, 1002, Tunis, Tunisia

    Abdellatif Selmi

  8. Facultad de Ingeniería, Universidad Católica de la Santísima Concepción, Concepción, Chile

    Nelson Maureira-Carsalade

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  1. Runqian Ma
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Correspondence to Aria Ghabussi, Yousef Zandi or Nelson Maureira-Carsalade.

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Ma, R., Karimzadeh, M., Ghabussi, A. et al. Assessment of composite beam performance using GWO–ELM metaheuristic algorithm. Engineering with Computers 38 (Suppl 3), 2083–2099 (2022). https://doi.org/10.1007/s00366-021-01363-1

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