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Predicting the impact of traffic–induced vibrations on buildings using artificial neural networks

Abstract

Traffic–induced vibrations may constitute a considerable load to a building, cause cracking of plaster, cracks in load–bearing elements or even a global structural collapse of the whole structure [1-4]. Vibrations measurements of real structures are costly and laborious, not justified in all cases. The aim of the paper is to create an original algorithm, to predict the negative dynamic impact on the examined residential building with a high probability. The model to forecast the impact of vibrations on buildings is based on artificial neural networks [5]. The author’s own field studies carried out according to the Polish standard [6] and literature examples [7- 10] have been used to create the algorithms. The results of the conducted analysis show that an artificial neural network can be considered a good tool to predict the impact of traffic–induced vibrations on residential buildings, with a sufficiently high reliability.

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Category:
Articles
Type:
artykuły w czasopismach
Published in:
MATEC Web of Conferences no. 219, pages 1 - 7,
ISSN: 2261-236X
Language:
English
Publication year:
2018
Bibliographic description:
Jakubczyk-Gałczyńska A.: Predicting the impact of traffic–induced vibrations on buildings using artificial neural networks// MATEC Web of Conferences -Vol. 219, (2018), s.1-7
DOI:
Digital Object Identifier (open in new tab) 10.1051/matecconf/201821904004
Verified by:
Gdańsk University of Technology

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