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- W32248825 abstract "Standard artificial neural networks and Bayesian neural networks (BNNs) are briefly discussed on example of a simple feed-forward layered neural networks (FLNN). Main ideas of the Bayesian approach and basics of the applied BNNs are presented in short. A study case corresponds to prediction of Displacement Response Spectrum inside buildings at the basement level (DRSb). Data for network training and testing were adopted as DRS corresponding to the preprocessed accelerograms. They were taken from measurements in the Legnica-Glogow Copperfield at monitored 5-storey buildings subjected to paraseismic excitations from explosives in nearby strip mines. Results of neural predictions by three NNs (standard FLNN trained by means of the conjugate gradient learning method, Simple Bayesian SBNN and Full Bayesian FBNN) are presented. The errors of predictions are on average on the level of 4% errors." @default.
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- W32248825 date "2006-01-01" @default.
- W32248825 modified "2023-09-24" @default.
- W32248825 title "Bayesian neural networks for prediction of response spectra" @default.
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