Performance assessment of a bio-inspired anomaly detection algorithm for unsupervised SHM: application to a Manueline masonry church Artigo Académico uri icon

autores

  • Barontini, Alberto
  • Paulo Jorge Rodrigues Amado Mendes
  • Maria Giovanna Masciotta
  • Amado Mendes, Paulo
  • Luis F. Ramos

data de publicação

  • janeiro 1, 2020