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This study investigates the applicability of feed-forward neural network model for prediction of damage in plate-like structures. The presented method is based on the static displacements as input parameters to the AI-based technique. The performance of the proposed method was evaluated by using cantilever plate containing one or several damages. The model results were compared using mean square errors. Obtained results show the capability of proposed method to detect damage in plate structures using feed-forward neural network model and static displacements which may be noisy or noise free.
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