Analysis of Taxi Supply and Demand Matching Degree Based on BP Neural Network

DOI

10.2991/icmmita-15.2015.97How to use a DOI?

Keywords

BP neural network; Wuhan taxi; supply and demand matching degree

Abstract

To analyze supply and demand matching degree of taxi resources in different periods in the long span, namely, with year as its measuring unit, this paper selects Wuhan city whose taxi ordering volume ranks in forefront [1] in China, analyzes the change law and development trend of supply and demand matching index as time goes on by using BP neural network algorithm, and concludes that the demand and supply matching degree of taxi before 2011 in Wuhan was high, the supply and demand matching ratio and matching index of taxi in Wuhan after 2012 significantly increased, the relationship between supply and demand was increasingly intense, and the supply of taxi in Wuhan would be difficult to meet the demand in future 5 years.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yajing Li
PY  - 2015/11
DA  - 2015/11
TI  - Analysis of Taxi Supply and Demand Matching Degree Based on BP Neural Network
BT  - Proceedings of the 2015 3rd International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 497
EP  - 501
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-15.2015.97
DO  - 10.2991/icmmita-15.2015.97
ID  - Li2015/11
ER  -