Exploratory Data Analysis and Data Envelopment Analysis of Urban Rail Transit
Use este enlace para citar
http://hdl.handle.net/2183/26642Coleccións
- GI-GAC - Artigos [192]
Metadatos
Mostrar o rexistro completo do ítemTítulo
Exploratory Data Analysis and Data Envelopment Analysis of Urban Rail TransitData
2020-08-07Cita bibliográfica
Taboada, G.L.; Han, L. Exploratory Data Analysis and Data Envelopment Analysis of Urban Rail Transit. Electronics 2020, 9, 1270.
Resumo
[Abstract]
This paper deals with the efficiency and sustainability of urban rail transit (URT) using exploratory data analytics (EDA) and data envelopment analysis (DEA). The first stage of the proposed methodology is EDA with already available indicators (e.g., the number of stations and passengers), and suggested indicators (e.g., weekly frequencies, link occupancy rates, and CO2 footprint per journey) to directly characterize the efficiency and sustainability of this transport mode. The second stage is to assess the efficiency of URT with two original models, based on a thorough selection of input and output variables, which is one of the key contributions of EDA to this methodology. The first model compares URT against other urban transport modes, applicable to route personalization, and the second scores the efficiency of URT lines. The main outcome of this paper is the proposed methodology, which has been experimentally validated using open data from the Transport for London (TfL) URT network and additional sources.
Palabras chave
Urban Rail Transit (URT)
Exploratory Data Analysis (EDA)
Data Envelopment Analysis (DEA)
Sustainable transport systems
Intelligent Transportation Systems (ITS)
Big-data applications
Exploratory Data Analysis (EDA)
Data Envelopment Analysis (DEA)
Sustainable transport systems
Intelligent Transportation Systems (ITS)
Big-data applications
Versión do editor
Dereitos
Atribución 4.0 España
ISSN
2079-9292