Simplified deep-learning approach for estimating the ultimate axial load of circular composite columns
Author:
Funder
All India Council for Technical Education
Publisher
Springer Science and Business Media LLC
Subject
Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s42107-023-00647-9.pdf
Reference44 articles.
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3. Avci-Karatas, C. (2019). Prediction of ultimate load capacity of concrete-filled steel tube columns using multivariate adaptive regression splines (MARS). Steel and Composite Structures, 33(4), 583–594. https://doi.org/10.12989/scs.2019.33.4.583
4. Behnood, A., & Golafshani, E. M. (2018). Predicting the compressive strength of silica fume concrete using hybrid artificial neural network with multi-objective grey wolves. Journal of Cleaner Production, 202, 54–64. https://doi.org/10.1016/j.jclepro.2018.08.065
5. Charalampakis, A. E., & Papanikolaou, V. K. (2021). Machine learning design of R/C columns. Engineering Structures, 226, 111412. https://doi.org/10.1016/j.engstruct.2020.111412
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