Balancing Composite Motion Optimization and Artificial Neural Network for the Prediction of Critical Load of Concrete-Filled Steel Tubes Under Axial Compression-Reference-Cited by-同舟云学术

Balancing Composite Motion Optimization and Artificial Neural Network for the Prediction of Critical Load of Concrete-Filled Steel Tubes Under Axial Compression

Published:2022-12-02 Issue: Volume: Page:290-296
ISSN:2367-3370
Container-title:Advances in Engineering Research and Application
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Author:

Duong Huan Thanh,Le Tien-Thinh,Nguyen Xuan Son,Le Minh Vuong,Phan Hieu Chi,Le Lu Minh,Nguyen Van Hai

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-22200-9_31

Reference12 articles.

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2. Le, T.-T.: Practical machine learning-based prediction model for axial capacity of square CFST columns. Mech. Adv. Mater. Struct. 29, 1–16 (2020). https://doi.org/10.1080/15376494.2020.1839608

3. Ho, N.X., Le, T.-T.: Effects of variability in experimental database on machine-learning-based prediction of ultimate load of circular concrete-filled steel tubes. Measurement 176, 109198 (2021). https://doi.org/10.1016/j.measurement.2021.109198

4. Ahmadi, M., Naderpour, H., Kheyroddin, A.: ANN model for predicting the compressive strength of circular steel-confined concrete. Int. J. Civ. Eng. 15, 213–221 (2017)

5. Duong, T.H., Le, T.-T., Nguyen, S.X., Le, M.V.: Adaptive-neuro-fuzzy-inference-system model for prediction of ultimate load of rectangular concrete-filled steel tubular columns. J. Intell. Fuzzy Syst. Preprint, 1–19 (2022). https://doi.org/10.3233/JIFS-201628

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