Economic valuation of traffic noise based on artificial neural networks
Abstract:
The poster presents a new approach to value the willingness to pay to reduce road noise annoyance using an artificial neural network (ANN) ensemble. The model pbkp_redicts, with adequate precision and accuracy, a willingness to pay range from subjetctive assessments of noise, a modeled noise exposure level, antd both demographic and socio-economic conditions. The results were compared with an ordered probit econometric model in terms of the performance mean relative error, and obtained a 85% better accuracy. The results of this study show that the model reach an adequate generalization level and can be applicable as a tool for valuing noise from transportation in order to obtain financial resources for action plans.
Año de publicación:
2016
Keywords:
Fuente:

Tipo de documento:
Other
Estado:
Acceso abierto
Áreas de conocimiento:
- Ciencia ambiental
- Ciencias de la computación
- Red neuronal artificial
Áreas temáticas:
- Comercio, comunicaciones, transporte
- Economía de la tierra y la energía
- Física aplicada