The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Classification of failure mode and prediction of shear strength for reinforced concrete beam-column joints using machine learning techniques
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Cites
Regularization and Variable Selection Via the Elastic Net
Zou, H., & Hastie, T. (2005) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2005.00503.x · Cited by 20,957
THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS
FISHER, R. A. (1936) · Annals of Eugenics · doi:10.1111/j.1469-1809.1936.tb02137.x · Cited by 15,227
Extreme Learning Machine for Regression and Multiclass Classification
Huang, G.-B., Zhou, H., Ding, X., & Zhang, R. (2012) · IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) · doi:10.1109/tsmcb.2011.2168604 · Cited by 5,550
Extreme learning machine: a new learning scheme of feedforward neural networks
Huang, G.-B., Zhu, Q.-Y., & Siew, C.-K. (2005) · 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541) · doi:10.1109/ijcnn.2004.1380068 · Cited by 4,084
Genetic Algorithms and Machine Learning
Goldberg, D. E., & Holland, J. H. (1988) · Machine Learning · doi:10.1023/a:1022602019183 · Cited by 3,193
Mangalathu, S., Heo, G., & Jeon, J. (2018) · Engineering Structures · doi:10.1016/j.engstruct.2018.01.053 · Cited by 301
Self-citationCritical uncertainty parameters influencing seismic performance of bridges using Lasso regression
Mangalathu, S., Jeon, J., & DesRoches, R. (2018) · Earthquake Engineering & Structural Dynamics · doi:10.1002/eqe.2991 · Cited by 175
Self-citationStatistical models for shear strength of RC beam‐column joints using machine‐learning techniques
Jeon, J., Shafieezadeh, A., & DesRoches, R. (2014) · Earthquake Engineering & Structural Dynamics · doi:10.1002/eqe.2437 · Cited by 134
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Cited by
Machine Learning for Structural Engineering: A State-of-the-Art Review
Thai, H.-T. (2022) · Structures · doi:10.1016/j.istruc.2022.02.003 · Cited by 748
Sun, H., Burton, H. V., & Huang, H. (2021) · Journal of Building Engineering · doi:10.1016/j.jobe.2020.101816 · Cited by 544
Mohtasham Moein, M., Saradar, A., Rahmati, K., Ghasemzadeh Mousavinejad, S. H., Bristow, J., Aramali, V., & Karakouzian, M. (2023) · Journal of Building Engineering · doi:10.1016/j.jobe.2022.105444 · Cited by 391
Rahman, J., Ahmed, K. S., Khan, N. I., Islam, K., & Mangalathu, S. (2021) · Engineering Structures · doi:10.1016/j.engstruct.2020.111743 · Cited by 346
Self-citationTapeh, A. T. G., & Naser, M. Z. (2023) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-022-09793-w · Cited by 320
On the application of machine learning techniques to derive seismic fragility curves
Kiani, J., Camp, C., & Pezeshk, S. (2019) · Computers & Structures · doi:10.1016/j.compstruc.2019.03.004 · Cited by 312
Classifying earthquake damage to buildings using machine learning
Mangalathu, S., Sun, H., Nweke, C. C., Yi, Z., & Burton, H. V. (2020) · Earthquake Spectra · doi:10.1177/8755293019878137 · Cited by 298
Self-citationKazemi, F., Asgarkhani, N., & Jankowski, R. (2023) · Soil Dynamics and Earthquake Engineering · doi:10.1016/j.soildyn.2023.107761 · Cited by 283
Feng, D.-C., Liu, Z.-T., Wang, X.-D., Jiang, Z.-M., & Liang, S.-X. (2020) · Advanced Engineering Informatics · doi:10.1016/j.aei.2020.101126 · Cited by 269
Architectural Technology Research Unit, D. O. A., Zain, M., Keawsawasvong, S., Department of Civil Engineering, T. S. O. E., Thongchom, C., Department of Civil Engineering, T. S. O. E., Sereewatthanawut, I., King Prajadhipok's Institute, B. 1., Usman, M., School of Civil and Environmental Engineering, N. U. O. S. A. T. (., et al. (2023) · Engineered Science · doi:10.30919/es1008 · Cited by 30
Metadata
- Authors
- Mangalathu, S., & Jeon, J.-S.
- Venue
- Engineering Structures
- Publisher
- Elsevier BV
- Published
- 2018-04
- Volume
- 160
- Pages
- 85-94
- ISSN
- 0141-0296 (ISSN-L)
- OpenAlex
- W2788697198
- Cited by
- 363
- References
- 8
- FWCI
- 14.87
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
