Prediction of building damage induced by tunnelling through an optimized artificial neural network

• Main Authors: Moosazadeh, S., Namazi, E., Aghababaei, H., Marto, A., Mohamad, H., Hajihassani, M.
• Format: Article
• Published: Springer London 2019
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047161551&doi=10.1007%2fs00366-018-0615-5&partnerID=40&md5=4e9c58609aa02661f6811a269626fd58; http://eprints.utp.edu.my/21567/
• Institution: Universiti Teknologi Petronas

Ground surface movement due to tunnelling in urban areas imposes strains to the adjacent buildings through distortion and rotation, and may consequently cause structural damage. The methods of building damage estimation are generally based on a two-stage procedure in which ground movement in the gre...