An Analysis of Energy Consumption for Transportation in Portuguese Cities Using Artificial Neural Networks

Empirical studies carried out in several parts of the world have highlighted the existence of a strong relationship between the physical planning of cities and energy use for transportation. Despite the economic and environmental costs produced by urban sprawl, several countries have not yet started to study the phenomenon in order to better understand it and to somehow control it. Thus, this study tries to bring a contribution to the subject through an analysis of the situation found in some of the main Portuguese cities, which however do not include Lisbon and Oporto. The main objective of this work is to identify the variables related to physical aspects of the cities and socioeconomic characteristics of urbanized areas in Portugal that significantly influence energy consumption for transportation. After the spatial and socioeconomic data were combined in a single database, they were analyzed using Artificial Neural Network models, in order to identify variables that are relevant to energy consumption for transportation, along with their relative weights. The results found in the current study confirmed the trend observed in several countries worldwide, in which the characteristics of urban form and population distribution played an important role influencing energy use for transportation.

• Corporate Authors:

  World Conference on Transport Research Society

  Secretariat, 14 Avenue Berthelot
  69363 Lyon cedex 07,   France 
• Authors:
  • Teixeira da Costa, Paula
  • Mendes, José Fernando Gomes
  • da Silva, Antonio Nelson Rodrigues
• Conference:
  • 10th World Conference on Transport Research
  • Location: Istanbul , Turkey
  • Date: 2004-7-4 to 2004-7-8
• Publication Date: 2004

Language

• English

Media Info

• Media Type: CD-ROM
• Features: Figures; Maps; References; Tables;
• Pagination: 18p
• Monograph Title: 10th World Conference on Transport Research

Subject/Index Terms

• TRT Terms: City planning; Energy; Energy consumption; Neural networks; Socioeconomic factors; Urban development; Urban sprawl; Urban transportation
• Geographic Terms: Portugal
• Subject Areas: Economics; Energy; Environment; Highways; Planning and Forecasting; Society; I15: Environment; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01087890
• Record Type: Publication
• Files: TRIS
• Created Date: Jan 30 2008 11:42AM