Neural Networks for the Simulation and Identification Analysis of Buildings Subjected to Paraseismic Excitations

Neural Networks for the Simulation and Identification Analysis of Buildings Subjected to Paraseismic Excitations

Krystyna Kuzniar (Pedagogical University of Cracow, Poland) and Zenon Waszczyszyn (Rzeszów University of Technology, Poland)
Copyright: © 2007 |Pages: 40
DOI: 10.4018/978-1-59904-099-8.ch016
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Abstract

The chapter deals with an application of neural networks to the analysis of vibrations of medium-height prefabricated buildings with load-bearing walls subjected to paraseismic excitations. Neural network technique was used for identification of dynamic properties of actual buildings, simulation of building responses to paraseismic excitations as well as for the analysis of response spectra. Mining tremors in strip mines and in the most seismically active mining regions in Poland with underground exploitation were the sources of these vibrations. On the basis of the experimental data obtained from the measurements of kinematic excitations and dynamic building responses of actual structures the training and testing patterns were formulated. It was stated that the application of neural networks enables us to predict the results with accuracy quite satisfactory for engineering practice. The results presented in this chapter lead to a conclusion that the neural technique gives new prospects of efficient analysis of structural dynamics problems related to paraseismic excitations.

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