The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
Machine learning methods in civil engineering: a systematic review
Open accessAbstract
Machine learning has found applications across a range of commercial enterprises. One of the exciting industries impacted by AI has been civil engineering. The aim of this paper is to review recent developments in AI as they relate to civil engineering. We highlight potential applications as well as the risks.
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From Artificial intelligence in civil engineering: emerging applications and opportunities (2025) · cites this paper as Kamolov et al., 2024
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Cites
New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution
Kamalov, F., Santandreu Calonge, D., & Gurrib, I. (2023) · Sustainability · doi:10.3390/su151612451 · Cited by 1,089
Applications of artificial intelligence for disaster management
Sun, W., Bocchini, P., & Davison, B. D. (2020) · Natural Hazards · doi:10.1007/s11069-020-04124-3 · Cited by 491
Machine Learning in Disaster Management: Recent Developments in Methods and Applications
Linardos, V., Drakaki, M., Tzionas, P., & Karnavas, Y. (2022) · Machine Learning and Knowledge Extraction · doi:10.3390/make4020020 · Cited by 319
The role of artificial neural network and machine learning in utilizing spatial information
Goel, A., Kumar, A., & Kumar, A. (2022) · Spatial Information Research · doi:10.1007/s41324-022-00494-x · Cited by 304
Artificial Intelligence in Civil Engineering
Lu, P., Chen, S., & Zheng, Y. (2012) · Mathematical Problems in Engineering · doi:10.1155/2012/145974 · Cited by 265
A new computational intelligence approach to detect autistic features for autism screening
Thabtah, F., Kamalov, F., & Rajab, K. D. (2018) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2018.06.009 · Cited by 209
Kamalov, F., Pourghebleh, B., Gheisari, M., Liu, Y., & Moussa, S. (2023) · Sustainability · doi:10.3390/su15043317 · Cited by 163
Tan, L., Guo, J., Mohanarajah, S., & Zhou, K. (2020) · Natural Hazards · doi:10.1007/s11069-020-04429-3 · Cited by 130
Fairness and accountability of AI in disaster risk management: Opportunities and challenges
Gevaert, C. M., Carman, M., Rosman, B., Georgiadou, Y., & Soden, R. (2021) · Patterns · doi:10.1016/j.patter.2021.100363 · Cited by 127
Forecasting significant stock price changes using neural networks
Kamalov, F. (2020) · Neural Computing and Applications · doi:10.1007/s00521-020-04942-3 · Cited by 125
Flagged first, then by citations
Research works printed but not linked: 8
- Yang, X., Xiaowei, J., & Hui, L. (2022). State-of-the-art and prospect of intelligent science and technology in civil engineering. Journal of Building Structures, 43(9), 23.
- Bao, Y., & Li, H. (2019). Artificial intelligence for civil engineering. Chin Civil Eng J, 52(5), 1-11.
- Singh, D. P., Srivastava, D., & Tiwari, A. K. (2023). A Critical Review on Sustainable Structural Optimization using Computational Approach.
- Zhang, C., Kim, J., Jeon, J., Xing, J., Ahn, C., Tang, P., & Cai, H. (2021). To- ward integrated human-machine intelligence for civil engineering: An interdisciplinary perspective. Computing in Civil Engineering 2021, 279-286. https://doi.org/10.1061/ 9780784483893.035 · DOI
- Liu, H., Zhang, F., Chen, Z., & Wang. (2024). Applied research status and prospects of artificial intelligence in civil engineering field. Journal of Civil and Environmental Engineer- ing.
- Singh, D. P., Srivastava, D., & Tiwari, A. K. (2023). A Critical Review on Sustainable Structural Optimization using Computational Approach.
- Shandilya, T., Agrawal, V., & Gupta, R. (2022, September). Role of Artificial Intelligence in improving structural performance: A Review. In IOP Conference Series: Earth and Environmental Science (Vol. 1086, No. 1, p. 012002). IOP Publishing. https://doi.org/ 10.1088/1755-1315/1086/1/012002 · DOI
- Linardos, V., Drakaki, M., Tzionas, P., & Karnavas, Y. L. (2022). Machine learning in disaster management: recent developments in methods and applications. Machine Learning and Knowledge Extraction, 4(2). https://doi.org/10.3390/ · DOI · Paper page
Cited by
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Artificial intelligence in civil engineering: emerging applications and opportunities
Nyokum, T., & Tamut, Y. (2025) · Frontiers in Built Environment · doi:10.3389/fbuil.2025.1622873 · Cited by 33
Metadata
- Authors
- Kamolov, S.
- Affiliations
- Technological University of Tajikistan (TJ)
- Corresponding author
- Kamolov, Saidjon
- Venue
- Annals of Mathematics and Computer Science
- Publisher
- Vertex Academic Press
- Published
- 2024-02-17
- Volume
- 21
- Pages
- 181-191
- ISSN
- 2789-7206 (ISSN-L)
- OpenAlex
- W4391918024
- Cited by
- 12
- References
- 55
- Citations by year
- 2026: 6 · 2025: 6
- FWCI
- 0.41
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Annals of Mathematics and Computer Science (publishedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Maintenance and Monitoring
- Physical Sciences › Engineering › Civil and Structural Engineering › Civil and Structural Engineering Research
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- machine learning, artificial intelligence, civil engineering applications, AI risks, civil engineering industry
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