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Descripción
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| In this paper, we present a new approach to value the willingness to pay to reduce road noise annoyance using an artificial neural network ensemble. The model predicts, with precision and accuracy, a range for willingness to pay from subjective assessments of noise, a modelled noise exposure level, and both demographic and socio-economic conditions. The results were compared to an ordered probit econometric model in terms of the performance mean relative error and obtained 85.7% better accuracy. The results of this study show that the applied methodology allows the model to reach an adequate generalisation level, and can be applicable as a tool for determining the cost of transportation noise in order to obtain financial resources for action plans. | |
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Internacional
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Si |
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JCR del ISI
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Si |
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Título de la revista
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Transportation Research Part D-Transport And Environment |
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ISSN
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1361-9209 |
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Factor de impacto JCR
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1,626 |
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Información de impacto
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Datos JCR del año 2013 |
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Volumen
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50C |
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DOI
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10.1016/j.trd.2016.10.020 |
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Número de revista
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Desde la página
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26 |
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Hasta la página
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39 |
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Mes
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ENERO |
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Ranking
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