Gordan, M. and Ghaedi, K. and Ismail, Zubaidah and Benisi, H. and Hashim, Huzaifa and Ghayeb, H.H. (2021) From conventional to sustainable SHM: implementation of artificial intelligence in the Department of Civil Engineering, University of Malaya. In: 3rd IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2021, 13-15 September 2021, Kota Kinabalu, Sabah.
Full text not available from this repository.Abstract
Computer-based technologies and their applications pervade everywhere in real life, especially in different fields of civil engineering. For example, conventional structural health monitoring (SHM) has been rapidly upgraded to sustainable SHM using artificial intelligence. It is because conventional approaches are challenged by real-time, low-cost, and quality-guaranteed SHM. In this direction, a number of innovative researches have been carried out in the Department of Civil Engineering, University of Malaya. This paper attempts to present the latest developments of SHM-based artificial intelligence in Structural Health Monitoring Research Group (StrucHMRSGroup) and Advance Shock and Vibration Research Group (ASVR). To this end, the applications of artificial neural networks, fuzzy logic, genetic algorithm, data mining, and regression analysis in SHM are presented with the aim of showing the efficiency of these methods. © 2021 IEEE.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Funders: | Fuzhou University [Grant no. IIRG007A-2019] |
| Uncontrolled Keywords: | Artificial intelligence; Data mining; Structural health monitoring; Sustainability |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | Faculty of Engineering > Department of Civil Engineering |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 13 Feb 2025 03:50 |
| Last Modified: | 13 Feb 2025 03:50 |
| URI: | http://eprints.um.edu.my/id/eprint/35643 |
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