During their lifecycle, bridge structures have to withstand various uncertainties loads such as wind, typhoon, accident loads, etc, which may pose serious threats to the integrity as well as the safety of the structure, especially when they induced significant damages to the structure. For many years, researchers have been trying to develop heath monitoring tools, which can identify accurately not only the location, but also the level of structural damage. In this paper, two novel avian-based optimization algorithms-Artificial Hummingbird Algorithm (AHA) and African Vulture Optimization Algorithm (AVOA) are reviewed for their feasibility in detecting structural damages in truss bridge. The accuracy of the proposed algorithms is compared against two other famous algorithms: Particle Swarm Optimization (PSO) and Cuckoo Search (CS). The results of the feasibility review for damage detection capability are discussed.
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