A NEURAL NETWORK BASED CAR OWNERSHIP MODEL
With the economic growth and the improvement of living standards, car ownership in China is increasing rapidly. It exerts enormous pressure on transportation services. It is necessary to forecast China car ownership for urban transport planning, transport infrastructure improvement and traffic management in terms of economic level, urban configuration, traffic situation, and car-concerned policies. In this paper, the main factors affecting car ownership are analyzed and a model to estimate car ownership in China city with the BP neural network technology is developed. The model can take the sudden effect of some external factors such as political and economic factors on car ownership into account.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/0784407304
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Corporate Authors:
American Society of Civil Engineers
1801 Alexander Bell Drive
Reston, VA United States 20191-4400 -
Authors:
- Yang, Z
- Feng, T
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Conference:
- Applications of Advanced Technologies in Transportation Engineering. Eighth International Conference
- Location: Beijing, China
- Date: 2004-5-26 to 2004-5-28
- Publication Date: 2004
Language
- English
Media Info
- Features: References; Tables;
- Pagination: p. 631-635
Subject/Index Terms
- TRT Terms: Automobile ownership; Economic growth; Infrastructure; Living conditions; Neural networks; Ownership; Traffic congestion; Traffic control; Transportation planning; Urban transportation; Vehicles
- Geographic Terms: China
- Subject Areas: Economics; Operations and Traffic Management; Planning and Forecasting; Public Transportation; Society; Vehicles and Equipment; I72: Traffic and Transport Planning;
Filing Info
- Accession Number: 00986154
- Record Type: Publication
- ISBN: 0784407304
- Files: TRIS
- Created Date: Feb 10 2005 12:00AM