Prediction of displacement of composite slab with profiled steel deck using artificial neural network
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s42107-024-01040-w.pdf
Reference48 articles.
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2. Abiodun, O. I., Jantan, A., Omolara, A. E., Dada, K. V., Mohamed, N. A. E., & Arshad, H. (2018). State-of-the-art in artificial neural network applications: A survey. Heliyon, 4(11), e00938. https://doi.org/10.1016/j.heliyon.2018.e00938
3. Ahmed, S. M., Avudaiappan, S., Sheet, I. S., Saavedra Flores, E. I., Pina, J. C., Yanez, S. J., & Guzmán, C. F. (2019). Prediction of longitudinal shear resistance of steel–concrete composite slabs. Engineering structures (Vol. 193, pp. 295–300). Elsevier. https://doi.org/10.1016/j.engstruct.2019.05.010
4. Al-deen, S., & Ranzi, G. (2015). Effects of non-uniform shrinkage on the long-term behaviour of composite steel–concrete slabs. International Journal of Steel Structures, 15(2), 415–432. https://doi.org/10.1007/s13296-015-6012-7
5. Almustafa, M. K., & Nehdi, M. L. (2021). Machine learning prediction of structural response for FRP retrofitted RC slabs subjected to blast loading. Engineering Structures, 244(June), 112752. https://doi.org/10.1016/j.engstruct.2021.112752
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