Intelligence Techniques Applied in Infrastructure, Engineering and Construction
This reprint comprises one Editorial and twenty-three peer-reviewed papers from the concluded Special Issue “Intelligent Techniques Applied in Infrastructure, Engineering and Construction” in Buildings. Together they capture the rapid transition of artificial intelligence, machine learning, and data...
保存先:
| フォーマット: | Online |
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| 言語: | 英語 |
| 出版事項: |
MDPI - Multidisciplinary Digital Publishing Institute
2025
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| 主題: | |
| オンライン･アクセス: | ONIX_20250812T110751_9783725843633_452 |
| タグ: |
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| _version_ | 1869522640495968256 |
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| collection | Directory of Open Access Books |
| description | This reprint comprises one Editorial and twenty-three peer-reviewed papers from the concluded Special Issue “Intelligent Techniques Applied in Infrastructure, Engineering and Construction” in Buildings. Together they capture the rapid transition of artificial intelligence, machine learning, and data-centric analytics from research prototypes to indispensable tools across the infrastructure lifecycle. The contributions address underground excavation, bridge and tunnel risk governance, ballastless-track monitoring, hybrid optimization of concrete thermodynamics, UAV-assisted defect localisation, explainable deep-learning for cost estimation, and the uptake of Fourth Industrial Revolution technologies on construction sites. Methodological advances range from ensemble classifiers, Bayesian networks and transformer-enhanced computer vision to physics-informed surrogate modelling and mixed-heuristic optimization, while materials investigated span ultra-high-performance concrete, fiber-reinforced polymers, unsaturated clayey sands and mechanically connected precast piles. By fusing domain knowledge with advanced algorithms, the articles demonstrate measurable gains in safety, efficiency, carbon reduction and lifecycle resilience, offering engineers and researchers actionable guidance for responsible, data-driven infrastructure practice. |
| format | Online |
| id | doab-20.500.12854ir-165697 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1656972025-08-12T10:08:01Z Intelligence Techniques Applied in Infrastructure, Engineering and Construction Liu, Kaiwen Wang, Tengfei Zhang, Xiaoning artificial intelligence machine learning smart construction infrastructure resilience civil engineering thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology This reprint comprises one Editorial and twenty-three peer-reviewed papers from the concluded Special Issue “Intelligent Techniques Applied in Infrastructure, Engineering and Construction” in Buildings. Together they capture the rapid transition of artificial intelligence, machine learning, and data-centric analytics from research prototypes to indispensable tools across the infrastructure lifecycle. The contributions address underground excavation, bridge and tunnel risk governance, ballastless-track monitoring, hybrid optimization of concrete thermodynamics, UAV-assisted defect localisation, explainable deep-learning for cost estimation, and the uptake of Fourth Industrial Revolution technologies on construction sites. Methodological advances range from ensemble classifiers, Bayesian networks and transformer-enhanced computer vision to physics-informed surrogate modelling and mixed-heuristic optimization, while materials investigated span ultra-high-performance concrete, fiber-reinforced polymers, unsaturated clayey sands and mechanically connected precast piles. By fusing domain knowledge with advanced algorithms, the articles demonstrate measurable gains in safety, efficiency, carbon reduction and lifecycle resilience, offering engineers and researchers actionable guidance for responsible, data-driven infrastructure practice. 2025-08-12T10:07:59Z 2025-08-12T10:07:59Z 2025 book ONIX_20250812T110751_9783725843633_452 9783725843633 9783725843640 https://directory.doabooks.org/handle/20.500.12854/165697 eng image/jpeg Attribution 4.0 International https://mdpi.com/books https://mdpi.com/books/pdfview/book/11149 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-4364-0 10.3390/books978-3-7258-4364-0 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725843633 9783725843640 414 open access |
| spellingShingle | artificial intelligence machine learning smart construction infrastructure resilience civil engineering thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Intelligence Techniques Applied in Infrastructure, Engineering and Construction |
| title | Intelligence Techniques Applied in Infrastructure, Engineering and Construction |
| title_full | Intelligence Techniques Applied in Infrastructure, Engineering and Construction |
| title_fullStr | Intelligence Techniques Applied in Infrastructure, Engineering and Construction |
| title_full_unstemmed | Intelligence Techniques Applied in Infrastructure, Engineering and Construction |
| title_short | Intelligence Techniques Applied in Infrastructure, Engineering and Construction |
| title_sort | intelligence techniques applied in infrastructure engineering and construction |
| topic | artificial intelligence machine learning smart construction infrastructure resilience civil engineering thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | artificial intelligence machine learning smart construction infrastructure resilience civil engineering thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | ONIX_20250812T110751_9783725843633_452 |