Ensemble Soft Computing Models for Prediction of Deflection of Steel–Concrete Composite Bridges
Author:
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
https://link.springer.com/content/pdf/10.1007/s13369-023-08474-5.pdf
Reference45 articles.
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3. Ngamkhanong, C.; Alzabeebee, S.; Keawsawasvong, S.; Thongchom, C.: Performance of different machine learning techniques in predicting the flexural capacity of concrete beams reinforced with FRP rods. Asian J. Civ. Eng. pp. 1–12 (2023)
4. Albostami, A.S.; Al-Hamd, R.K.S.; Alzabeebee, S.; Minto, A.; Keawsawasvong, S.: Application of soft computing in predicting the compressive. Strength of Self-Compacted Concrete Containing Recyclable Aggregate (2023)
5. Al Hamd, R.K.S.; Alzabeebee, S.; Cunningham, L.S.; Gales, J.: Bond behaviour of rebar in concrete at elevated temperatures: a soft computing approach. Fire Mater. (2022)
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1. Prediction of central deflection and slenderness limit for lateral stability of simply supported concrete beam using machine learning techniques;Asian Journal of Civil Engineering;2024-07-26
2. Probabilistic analysis of simply supported concrete beam using machine learning techniques: a comparative study;Asian Journal of Civil Engineering;2024-03-27
3. Using machine learning algorithms for predicting bridge vertical deflection;Proceedings of the Institution of Civil Engineers - Engineering and Computational Mechanics;2024-03-01
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