Traffic-induced vibrations may cause the cracking of plaster, damage to structural elements and, in extreme cases, may even lead to the structural collapse of residential buildings. The aim of this article is to analyse the effectiveness of a method of forecasting the impact of vibrations on residential buildings using the concept of artificial intelligence. The article presents several alternative forecasting systems for which it is not necessary to carry out laborious and costly measurement tests. The results show that artificial neural networks can be an effective tool for estimating the impact of traffic-induced vibrations on buildings; however, more cases need to be analysed in order to validate the system.

Traffic-induced vibrations may cause the cracking of plaster, damage to structural elements and, in extreme cases, may even lead to the structural collapse of residential buildings. The aim of this article is to analyse the effectiveness of a method of forecasting the impact of vibrations on residential buildings using the concept of artificial intelligence. The article presents several alternative forecasting systems for which it is not necessary to carry out laborious and costly measurement tests. The results show that artificial neural networks can be an effective tool for estimating the impact of traffic-induced vibrations on buildings; however, more cases need to be analysed in order to validate the system.