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Application of Transfer Learning to Predict Structure"s Seismic Responses Before and After Retrofit
Hoang Dang-Vu(당부황),Lee, Kihak(이기학) 한국콘크리트학회 2021 한국콘크리트학회 학술대회 논문집 Vol.33 No.2
In seismic engineering, Machine Learning (ML) application has recently shown beneficial advantages in predicting structural responses and assessing its performance from collect data. Transfer learning is a research problem of ML that is capable of storing the knowledge gained from the training process of a task and applying that to the related task. This study aims to apply transfer learning to develop a surrogate model predict structural responses after retrofit by using the knowledge gained from its before retrofit counterpart developed in previous research.