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To achieve this goal, shm employs different system identification and model updating techniques to learn from and incorporate noisy data into numerical and mechanical models. Igor kavrakov, samuel tesfaye, guido morgenthal (2019) Machine learning models trained with structural health monitoring data have become a powerful tool for system identification

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Two reasons can explain this behavior A fluid and a solid First, because l2 has a larger learning data set (three curvatures vs one deflection) and second, because supplying the regression derivatives (i.e

Curvatures) contains more information about the system than the actual regress

Most of my research work revolves around dynamics of structures and wind engineering, computational fluid dynamics, system identification, and vehicle and pedestrian loading. Dynamics system identification through operational modal analysis, involving extraction of modal properties (frequencies, damping, shapes) from acceleration measurements using the stochastic subspace identification method.