Generative Adversarial Networks for Data Generation in Structural Health Monitoring. (arXiv:2112.08196v2 [cs.LG] UPDATED)

Structural Health Monitoring (SHM) has been continuously benefiting from the
advancements in the field of data science. Various types of Artificial
Intelligence (AI) methods have been utilized for the assessment and evaluation
of civil structures. In AI, Machine Learning (ML) and Deep Learning (DL)
algorithms require plenty of datasets to train; particularly, the more data DL
models are trained with, the better output it yields. Yet, in SHM applications,
collecting data from civil structures through sensors is expensive and
obtaining …

arxiv data generative adversarial networks health monitoring networks