A neural network based car ownership model


== Abstract ==

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.


== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.1061/40730(144)117 http://dx.doi.org/10.1061/40730(144)117]

* [http://ascelibrary.org/doi/pdf/10.1061/40730%28144%29117 http://ascelibrary.org/doi/pdf/10.1061/40730%28144%29117],
: [http://dx.doi.org/10.1061/40730(144)117 http://dx.doi.org/10.1061/40730(144)117]

* [https://www.narcis.nl/publication/RecordID/oai%3Apure.tue.nl%3Apublications%2F2841b86d-c848-4182-95a9-9687ed476c86 https://www.narcis.nl/publication/RecordID/oai%3Apure.tue.nl%3Apublications%2F2841b86d-c848-4182-95a9-9687ed476c86],
: [https://ascelibrary.org/doi/abs/10.1061/40730%28144%29117 https://ascelibrary.org/doi/abs/10.1061/40730%28144%29117],
: [https://trid.trb.org/view/749834 https://trid.trb.org/view/749834],
: [https://core.ac.uk/display/158754637 https://core.ac.uk/display/158754637],
: [https://academic.microsoft.com/#/detail/2001131303 https://academic.microsoft.com/#/detail/2001131303]