Performance evaluation of the artificial hummingbird algorithm in the problem of structural damage identification

Recently, Structural Health Monitoring (SHM) has become a critical component of the maintenance and safety of lifeline infrastructures such as dams, skyscrapers, and bridges, thanks to its ability to detect structural failures at the early stages. In this paper, we evaluate the performance of the SHM damage identification tool using a novel metaheuristic algorithm called the Artificial Hummingbird Algorithm (AHA).