Neural networks for the analysis of mine-induced building vibrations
Journal Title: Computer Assisted Methods in Engineering and Science - Year 2011, Vol 18, Issue 3
Abstract
A study of the capabilities of artificial neural networks in respect of selected problems of the analysis of mine-induced building vibrations is presented. Neural network technique was used for the prediction of building fundamental natural period, mapping of mining tremors parameters into response spectra from ground vibrations, soil-structure interaction analysis, simulation of building response to seismic- type excitation. On the basis of the experimental data obtained from the measurements of kinematic excitations and dynamic responses of actual structures, training and testing patterns of neural networks were formulated. The obtained results lead to a conclusion that the neural technique gives possibility of efficient, accurate enough for engineering, analysis of structural dynamics problems related to mine-induced excitations.
Authors and Affiliations
Krystyna Kuźniar
Formation of graph models for regular finite element meshes. (Received in the final form September 21, 2009)
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Regularization using truncated singular value decomposition for estimating the Fourier spectrum of a noised space distribution over an extended support
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Identification of solidification process parameters. (Received in the final form November 12, 2010)
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The method of the fundamental solutions and its modifications for electromagnetic field problems. (Received in the final form January 14, 2009)
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Neural modelling of compactibility characteristics of cohesionless soil. (Received in the final form July 30, 2010)
Compaction is the method of in-situ soil modification to improve its engineering properties. Two key compactibility parameters are: the maximum dry density ρd max and the corresponding optimum water content wopt. They ar...