Artificial Intelligence (ai) Approaches In Supplier Selection: A Systematic Review With Bibliometric Analysis
- Damage assessment of post-disaster built environments is critical in emergency response and recovery processes. Artificial intelligence is increasingly used in this field thanks to its ability to quickly analyses large, diverse, complex data and automate decision processes. This study evaluates the research trends, methods, and data utilization strategies in artificial intelligence-based structural damage assessment by examining 464 academic publications published between 2000 and 2024 through bibliometric analysis. The Web of Science Core Collection database data were analyzed using VOSviewer 1.6.20 and Microsoft Excel 2023. The analyses were based on the number of citations normalized by publication year. The findings reveal that the studies are mainly focused on earthquake-related issues, and the most common artificial intelligence techniques are supervised learning and deep learning architectures. Satellite imagery, UAV data, and 3D point clouds are the most frequently used data sources. The study summarizes the field's current state and provides directions for future research.
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