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In particular, the developed methodology uses the Analytic Hierarchy Process as a multi-criteria analysis method. The Multi-criteria Analysis proved to be the best solution both for completeness and versatility. The decision to use this method originates from an in-depth study of the state of the art regarding the issue of noise pollution related to transport infrastructures in Italy and at a European level. The research develops a guideline based on an already known methodology applied in other fields, which has been adapted to the above-mentioned topic: the multi-criteria analysis.
Noise mapping series#
The aim of the paper is to define a method for evaluating infrastructural interventions for the mitigation of noise generated by roads based on multi-criteria analysis which considers a series of parameters (environmental, social, economic and health) that could give broader evaluations than just economic convenience. The results also showed that in noise prediction based on the neural network-based model, the independent variables of train speed and distance from the center of the route are essential in predicting. The results showed the high efficiency of EANN models in noise prediction so that the prediction accuracy of 95.6% was reported. This study tried to model the maximum A-weighted noise pressure level with the information obtained from field measurements by Emotional artificial neural network (EANN) models and compare the results with linear and logarithmic regression models. The evaluation of railway performance cannot be imagined without measuring and managing noise. Considering the development of railway lines in underdeveloped countries, identifying and modeling the causes of vibrations and noise of rail transportation is of particular importance. For this reason, up-to-date knowledge seeks to find the causes of noise in various industries and thus prevent it as much as possible. Noise is considered one of the most critical environmental issues because it endangers the health of living organisms. See the Scimago widget by clicking the following link: Noise Mapping is ranked in Q2 in Acoustics and Ultrasonics category, according to Clarivate Analytics. Noise Mapping is indexed in Web of Science Core Collection (Emerging Sources Citation Index) and is accepted for inclusion in Scopus – Elsevier. As a result, the journal is set to acquire a growing reputation as the main publication in the field of noise mapping, thus leading to a significant Impact Factor. Potential readers are scientists, practitioners and public bodies representatives (for example environmental protection agencies) carrying out research and/or interested in environmental noise mapping, planning and control issues.Įver since its inception, Noise Mapping has been offering fast and comprehensive peer-review, while featuring prominent researchers among its Advisory Board. The goal of the journal is to be the first and main publishing option for authors writing on noise mapping and related topics, and a hub integrating the relevant research community in the field of environmental noise and soundscape studies. Papers concerning noise mapping of emissions from the following sources are welcome for publication: classification, evaluation and preservation of quiet areas.outdoor soundscape studies and mapping.actions and communications to increase public awareness of environmental noise issues.evaluation of environmental noise exposure.evaluation of noise mitigation actions.
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