19 citations as recorded by crossref.

1. Neural networks for the rapid seismic assessment of existing moment-frame RC buildings L. Stefanini et al. 10.1016/j.ijdrr.2021.102677
2. School buildings performance in 7.7 Mw and 7.6 Mw catastrophic earthquakes in southeast of Turkey M. Ozturk et al. 10.1016/j.jobe.2023.107810
3. Assessing embodied carbon of flat slab buildings – An ANN-integrated optimization methodology H. Trinh et al. 10.1016/j.jclepro.2024.142377
4. Prediction of energy absorption capability in fiber reinforced self-compacting concrete containing nano-silica particles using artificial neural network H. Tavakoli et al. 10.1590/S1679-78252014000600004
5. An evaluation of effective design parameters on earthquake performance of RC buildings using neural networks M. Arslan 10.1016/j.engstruct.2010.03.010
6. State-of-the-art review: Reduction factor of traditional steel moment resisting, braced or eccentrically braced systems M. Hassan 10.1016/j.istruc.2021.11.028
7. Damage mechanics based model for low-rise infilled RC frames incorporating neural networks K. Abou El-Ftooh et al. 10.1108/EC-05-2015-0140
8. Drift Reliability Assessment of a Four Storey Frame Residential Building Under Seismic Loading Considering Multiple Factors A. Sil & T. Longmailai 10.1007/s40030-017-0216-0
9. Does a Single ANN Properly Predict Pushover Response Parameters of Low-, Medium- and High-Rise Infilled RC Frames? K. El-Ftooh et al. 10.1007/s13369-018-3195-1
10. Optimum seismic performance estimation of integrated multiple steel pipes bridge pier connected by shear panel damper with ANN method A. Fajar et al. 10.1051/matecconf/201925802011
11. Prediction of punching shear strength of slab-column connections: A comprehensive evaluation of machine learning and deep learning based approaches S. Derogar et al. 10.1080/15376494.2022.2134950
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13. Shear strength estimation of RC deep beams using the ANN and strut-and-tie approaches G. Yavuz 10.12989/sem.2016.57.4.657
14. Application of artificial neural networks for dynamic analysis of building frames S. Joshi et al. 10.12989/cac.2014.13.6.765
15. Neural networks for inelastic distortional buckling capacity assessment of steel I-beams S. Tohidi & Y. Sharifi 10.1016/j.tws.2015.04.023
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18. Prediction of combined effects of fibers and nanosilica on the mechanical properties of self-compacting concrete using artificial neural network H. Tavakoli et al. 10.1590/S1679-78252014001100002
19. Design forces for groups of six cylindrical silos by artificial neural network modelling S. Yuksel & M. Arslan 10.1680/stbu.10.00049