Integrating AI and statistical methods for enhancing civil structural practices: current trends, practical issues, and future direction
The integration of artificial intelligence (AI) and statistical methods has revolutionized civil engineering by enhancing accuracy, efficiency, and reliability in various processes. This review systematically examines how advanced optimization techniques, including artificial neural networks (ANNs)...
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| Format: | Article |
| Language: | English |
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Gruppo Italiano Frattura
2024-10-01
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| Series: | Fracture and Structural Integrity |
| Subjects: | |
| Online Access: | https://fracturae.com/index.php/fis/article/view/5120 |
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| _version_ | 1825206705493901312 |
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| author | Asraar Anjum Meftah Hrairi Abdul Aabid Shaikh Noorfazrina Yatim Maisarah Ali |
| author_facet | Asraar Anjum Meftah Hrairi Abdul Aabid Shaikh Noorfazrina Yatim Maisarah Ali |
| author_sort | Asraar Anjum |
| collection | DOAJ |
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The integration of artificial intelligence (AI) and statistical methods has revolutionized civil engineering by enhancing accuracy, efficiency, and reliability in various processes. This review systematically examines how advanced optimization techniques, including artificial neural networks (ANNs), Design of Experiments (DOE), and fuzzy logic (FL), are transforming civil engineering practices. It emphasizes the significant roles these methods play in addressing modern challenges such as structural health monitoring, damage detection, seismic design optimization, and concrete condition assessment. The review delves into case studies and real-world applications, showcasing the potential of these methods to create more resilient, sustainable, and cost-effective infrastructures. It critically examines the limitations and scalability of these techniques, identifying gaps in current research and practical challenges in real-world applications. The investigation also highlights the need for substantial computational resources, data privacy, security, and software interoperability. By addressing these issues, the review not only shows advancements in optimization techniques but also outlines future research directions, aiming to bridge the gap between theoretical developments and practical applications in civil engineering. This review serves as an essential resource for researchers, professionals, and policymakers interested in leveraging optimization techniques to advance civil engineering practices.
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| format | Article |
| id | doaj-art-39cb69c76bf94c11b8dbcc8ea5777729 |
| institution | Kabale University |
| issn | 1971-8993 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | Gruppo Italiano Frattura |
| record_format | Article |
| series | Fracture and Structural Integrity |
| spelling | doaj-art-39cb69c76bf94c11b8dbcc8ea57777292025-02-07T06:12:26ZengGruppo Italiano FratturaFracture and Structural Integrity1971-89932024-10-011971Integrating AI and statistical methods for enhancing civil structural practices: current trends, practical issues, and future directionAsraar Anjum0Meftah Hrairi1https://orcid.org/0000-0003-3598-8795Abdul Aabid Shaikh2https://orcid.org/0000-0002-4355-9803Noorfazrina Yatim3Maisarah Ali4Department of Mechanical and Aerospace Engineering, Faculty of Engineering, International Islamic University Malaysia, P.O. Box 10, 50728, Kuala Lumpur, MalaysiaDepartment of Mechanical and Aerospace Engineering, Faculty of Engineering, International Islamic University Malaysia, P.O. Box 10, 50728, Kuala Lumpur, MalaysiaDepartment of Engineering Management, College of Engineering, Prince Sultan University, PO BOX 66833, Riyadh 11586, Saudi ArabiaDepartment of Mechanical and Aerospace Engineering, Faculty of Engineering, International Islamic University Malaysia, P.O. Box 10, 50728, Kuala Lumpur, MalaysiaDepartment of Civil Engineering, Faculty of Engineering, International Islamic University Malaysia, P.O. Box 10, 50728, Kuala Lumpur, Malaysia The integration of artificial intelligence (AI) and statistical methods has revolutionized civil engineering by enhancing accuracy, efficiency, and reliability in various processes. This review systematically examines how advanced optimization techniques, including artificial neural networks (ANNs), Design of Experiments (DOE), and fuzzy logic (FL), are transforming civil engineering practices. It emphasizes the significant roles these methods play in addressing modern challenges such as structural health monitoring, damage detection, seismic design optimization, and concrete condition assessment. The review delves into case studies and real-world applications, showcasing the potential of these methods to create more resilient, sustainable, and cost-effective infrastructures. It critically examines the limitations and scalability of these techniques, identifying gaps in current research and practical challenges in real-world applications. The investigation also highlights the need for substantial computational resources, data privacy, security, and software interoperability. By addressing these issues, the review not only shows advancements in optimization techniques but also outlines future research directions, aiming to bridge the gap between theoretical developments and practical applications in civil engineering. This review serves as an essential resource for researchers, professionals, and policymakers interested in leveraging optimization techniques to advance civil engineering practices. https://fracturae.com/index.php/fis/article/view/5120Optimization TechniquesArtificial Intelligence (AI)Civil StructuresFuzzy LogicDesign of Experiments (DOE) |
| spellingShingle | Asraar Anjum Meftah Hrairi Abdul Aabid Shaikh Noorfazrina Yatim Maisarah Ali Integrating AI and statistical methods for enhancing civil structural practices: current trends, practical issues, and future direction Fracture and Structural Integrity Optimization Techniques Artificial Intelligence (AI) Civil Structures Fuzzy Logic Design of Experiments (DOE) |
| title | Integrating AI and statistical methods for enhancing civil structural practices: current trends, practical issues, and future direction |
| title_full | Integrating AI and statistical methods for enhancing civil structural practices: current trends, practical issues, and future direction |
| title_fullStr | Integrating AI and statistical methods for enhancing civil structural practices: current trends, practical issues, and future direction |
| title_full_unstemmed | Integrating AI and statistical methods for enhancing civil structural practices: current trends, practical issues, and future direction |
| title_short | Integrating AI and statistical methods for enhancing civil structural practices: current trends, practical issues, and future direction |
| title_sort | integrating ai and statistical methods for enhancing civil structural practices current trends practical issues and future direction |
| topic | Optimization Techniques Artificial Intelligence (AI) Civil Structures Fuzzy Logic Design of Experiments (DOE) |
| url | https://fracturae.com/index.php/fis/article/view/5120 |
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