Bus line classification using neural networks

Authors

Felipe Jiménez
Francisco Serradilla
Alfonso Román
José Eugenio Naranjo

Document Type

Journal Article

Publication Date

2014

Subject Area

place - urban, mode - bus, planning - network design, planning - route design

Keywords

Cluster, Urban buses, Neural network, Bootstrap method

Abstract

Grouping urban bus routes is necessary when there are evidences of significant differences among them. In Jiménez et al. (2013), a reduced sample of routes was grouped into clusters utilizing kinematic measured data. As a further step, in this paper, the remaining urban bus routes of a city, for which no kinematic measurements are available, are classified. For such purpose we use macroscopic geographical and functional variables to describe each route, while the clustering process is performed by means of a neural network. Limitations caused by reduced training samples are solved using the bootstrap method.

Rights

Permission to publish the abstract has been given by Elsevier, copyright remains with them.

Comments

Transportation Research Part D Home Page:

http://www.sciencedirect.com/science/journal/13619209

Recommended Citation

Jiménez, F., Serradilla, F., Román, A. & Naranjo, J. E. (2014). Bus line classification using neural networks. Transportation Research Part D: Transport and Environment, Vol. 30, pp. 32–37.