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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 국제구조공학회 Steel and Composite Structures, An International Journal Steel and Composite Structures, An International Journal Vol.33 No.3
- 발행연도
- 2019.1
- 수록면
- 319 - 332 (14page)
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초록· 키워드
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This study is aimed to predict the behaviour of channel shear connectors in composite floor systems at different temperatures. For this purpose, a soft computing approach is adopted. Two novel intelligence methods, including an Extreme Learning Machine (ELM) and a Genetic Programming (GP), are developed. In order to generate the required data for the intelligence methods, several push-out tests were conducted on various channel connectors at different temperatures. The dimension of the channel connectors, temperature, and slip are considered as the inputs of the models, and the strength of the connector is predicted as the output. Next, the performance of the ELM and GP is evaluated by developing an Artificial Neural Network (ANN). Finally, the performance of the ELM, GP, and ANN is compared with each other. Results show that ELM is capable of achieving superior performance indices in comparison with GP and ANN in the case of load prediction. Also, it is found that ELM is not only a very fast algorithm but also a more reliable model.
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참고문헌 (105)
참고문헌 신청
Abedini, M. / 2017 / Evaluation of concrete structures reinforced with fiber reinforced polymers bars : a review / J. Asian Sci. Res 7(5):165
Abedini, M. / 2019 / Large Deflection Behavior Effect in Reinforced Concrete Columns Exposed to Extreme Dynamic Loads
Ali, T. / 2015 / Applications of the ANFIS and LR models in the prediction of shear connection in composite beams/Ali Toghroli
Meysam Alizamir / 2018 / An Artificial Neural Network - Particle Swarm Optimization (ANN- PSO) Approach to Predict Heavy Metals Contamination in Groundwater Resources / Jundishapur Journal of Health Sciences 10(2)
Arabnejad Khanouki, M. M. / 2011 / Behavior of through beam connections composed of CFSST columns and steel beams by finite element studying / Adv. Mater. Res 168:2329~2333
Abedini, M. / 2019 / Large Deflection Behavior Effect in Reinforced Concrete Columns Exposed to Extreme Dynamic Loads
Ali, T. / 2015 / Applications of the ANFIS and LR models in the prediction of shear connection in composite beams/Ali Toghroli
Meysam Alizamir / 2018 / An Artificial Neural Network - Particle Swarm Optimization (ANN- PSO) Approach to Predict Heavy Metals Contamination in Groundwater Resources / Jundishapur Journal of Health Sciences 10(2)
Arabnejad Khanouki, M. M. / 2011 / Behavior of through beam connections composed of CFSST columns and steel beams by finite element studying / Adv. Mater. Res 168:2329~2333
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