@inproceedings{c95814515a7247279df7770c9ce95957,
title = "Neural networks for the identification of linear dynamical model of a five story building",
abstract = "Presents the results of utilizing neural networks to provide an efficient computational model for a dynamical system. Neural networks are used for parameter identification of multistorey buildings. The networks were trained and tested using experimental data measured on building models. The measurements consist of acceleration time-histories taken at the base of the buildings and at the various floor levels. It is demonstrated that, once the initial learning phase is completed, the network can provide instantaneous identification of system parameters when presented with different acceleration records.",
author = "M. Elkordy and R. Ghanem and Lee, \{G. C.\}",
note = "Publisher Copyright: {\textcopyright} 1993 IEEE.; 2nd International Symposium on Uncertainty Modeling and Analysis, ISUMA 1993 ; Conference date: 25-04-1993 Through 28-04-1993",
year = "1993",
doi = "10.1109/ISUMA.1993.366784",
language = "English",
series = "Proceedings - 2nd International Symposium on Uncertainty Modeling and Analysis, ISUMA 1993",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "98--103",
booktitle = "Proceedings - 2nd International Symposium on Uncertainty Modeling and Analysis, ISUMA 1993",
address = "United States",
}