Forecasting Urban Rail Transit Vehicle Interior Noise and Its Applications in Railway Alignment Design

In this study, a data-driven interior noise prediction model is developed for vehicles on an urban rail transit system based on random forest (RF) and a vehicle/track coupling dynamic model (VTCDM). The proposed prediction model can evaluate and optimize the sustainability of railway alignment from...

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Bibliographic Details
Main Authors: Yifeng Wang, Ping Wang, Zihan Li, Zhengxing Chen, Qing He
Format: Article
Language:English
Published: Hindawi-Wiley 2020-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2020/5896739