Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/32350
Title: Estimation of AADT from short period counts in Hong Kong - a comparison between neural network method and regression analysis
Authors: Lam, WHK 
Xu, J
Issue Date: 2000
Publisher: John Wiley & Sons
Source: Journal of advanced transportation, 2000, v. 34, no. 2, p. 249-268 How to cite?
Journal: Journal of advanced transportation 
Abstract: The average annual daily traffic (AADT) volumes can be estimated by using a short period count of less than twenty-four hour duration. In this paper, the neural network method is adopted for the estimation of AADT from short period counts and for the determination of the most appropriate length of counts. A case study is carried out by analysing data at thirteen locations on trunk roads and primary roads in urban area of Hong Kong. The estimation accuracy is also compared with the one obtained by regression analysis approach. The results show that the neural network approach consistently performed better than the regression analysis approach.
URI: http://hdl.handle.net/10397/32350
ISSN: 0197-6729
EISSN: 2042-3195
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