Gordan, Meisam and Ong, Zhi Chao and Sabbagh-Yazdi, Saeed-Reza and Lai, Khin Wee and Ghaedi, Khaled and Ismail, Zubaidah (2022) From cognitive bias toward advanced computational intelligence for smart infrastructure monitoring. Frontiers in Psychology, 13. ISSN 1664-1078, DOI https://doi.org/10.3389/fpsyg.2022.846610.
Full text not available from this repository.Abstract
Visual inspections have been typically used in condition assessment of infrastructure. However, they are based on human judgment and their interpretation of data can differ from acquired results. In psychology, this difference is called cognitive bias which directly affects Structural Health Monitoring (SHM)-based decision making. Besides, the confusion between condition state and safety of a bridge is another example of cognitive bias in bridge monitoring. Therefore, integrated computer-based approaches as powerful tools can be significantly applied in SHM systems. This paper explores the relationship between the use of advanced computational intelligence and the development of SHM solutions through conducting an infrastructure monitoring methodology. Artificial Intelligence (AI)-based algorithms, i.e., Artificial Neural Network (ANN), hybrid ANN-based Imperial Competitive Algorithm, and hybrid ANN-based Genetic Algorithm, are developed for damage assessment using a lab-scale composite bridge deck structure. Based on the comparison of the results, the employed evolutionary algorithms could improve the prediction error of the pre-developed network by enhancing the learning procedure of the ANN.
| Item Type: | Article |
|---|---|
| Funders: | Universiti Malaya (IIRG007A-2019), Universiti Malaya (IIRG007B-2019) |
| Uncontrolled Keywords: | Cognitive bias; Infrastructure health monitoring; Bridge monitoring; Artificial intelligence; Safety |
| Subjects: | B Philosophy. Psychology. Religion > BF Psychology Q Science > Q Science (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TJ Mechanical engineering and machinery |
| Divisions: | Faculty of Engineering > Biomedical Engineering Department Faculty of Engineering > Department of Civil Engineering Faculty of Engineering > Department of Mechanical Engineering |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 10 Sep 2023 02:58 |
| Last Modified: | 10 Sep 2023 02:58 |
| URI: | http://eprints.um.edu.my/id/eprint/42958 |
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