Neural based contingent valuation of road traffic noise

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. (C) 2016 Elsevier Ltd. All rights reserved.