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This document discusses a proposed data-driven framework for identifying structural loads from measured responses, addressing the challenges of non-uniqueness and noise sensitivity in the inverse problem of structural dynamics. The approach utilizes machine learning techniques to create a supervised learning model that maps response features to applied loading conditions, facilitating rapid load identification and real-time monitoring. The methodology is particularly beneficial for complex structures where

Author

sri lowkya muktha sapram

Language

EN