Abstract
The paper outlines a methodological approach for the quantitative analysis of the level of noise produced on and by transport infrastructure in urban settings. Traffic-related noise is a source of pollution which can cause severe damage to communities in terms of health and social welfare. It is thus necessary to develop adequate and specific mathematical tools to reproduce or simulate different acoustic scenarios. An analysis is presented of the acoustic data measured in the metropolitan area of the Straits of Messina (Italy), which for its location is always subject to heavy traffic flows in transit between Sicily and the mainland (Calabria). An integrated neural-fuzzy approach to assess traffic noise, which was calibrated with the field data, is also proposed. The application of this model is compared with the traditional regressive prediction models known in the literature and the results are presented.
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