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Filtering by: Alternative title ssim Report no. 73-9 Conference Section/Track MS 40: Artificial Intelligence & Machine Learning in Design and Assessment of Structures License Attribution 4.0 (CC BY 4.0)

Structural Damage Prediction Under Seismic Sequence Using Neural Networks

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Lazaridis, Petros C., Kavvadias, Ioannis E., Demertzis, Konstantinos, Iliadis, Lazaros, Papaleonidas, Antonios, Vasiliadis, Lazaros K., and Elenas, Anaxagoras

Abstract:

Advanced machine learning algorithms, such as neural networks, have the potential to be successfully applied to many areas of system modelling. Several studies have been already conducted on forecasting structural damage due to individual earthquakes, ignoring the influence of seismic sequences, using neural networks. In the present study, an ensemble...

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Conference Proceeding

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successive earthquakes. Also, more recently, Kavvadias et al. [8] and Zhou et al. [9] investigated the

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Structural Damage Prediction Under Seismic Sequence Using Neural Networks

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