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

Abstrakt

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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Informacje szczegółowe

Kategoria:
Aktywność konferencyjna
Typ:
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Tytuł wydania:
2nd Baltic Conference for Students and Young Researchers (BalCon 2018) strony 1 - 7
Język:
angielski
Rok wydania:
2018
Opis bibliograficzny:
Jakubczyk-Gałczyńska A.: Predicting the impact of traffic–induced vibrations on buildings using artificial neural networks// 2nd Baltic Conference for Students and Young Researchers (BalCon 2018)/ : , 2018, s.1-7
DOI:
Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1051/matecconf/201821904004
Weryfikacja:
Politechnika Gdańska

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