DocumentCode :
735463
Title :
Vessel traffic flow prediction model based on complex network
Author :
Wen Hang ; Mengyuan Xu ; Xingyuan Chen ; Shaolong Zhou
Author_Institution :
Sch. of Navig., Wuhan Univ. of Technol., Wuhan, China
fYear :
2015
fDate :
25-28 June 2015
Firstpage :
473
Lastpage :
476
Abstract :
A complex network structure can describe many real systems, ports system meet characteristics of complex network system. This paper built a new weighted port evolutional network model using vessel traffic flow as the relevance rating affecting port evolution, on the basis of this. It proposed a port vessel traffic flow forecasting model based on complex networks and used vessel traffic volume of Tianjin Port during 2002-2013 years as the experimental data and ultimately verified and predicted it through the use of forecasting model parameters obtained by fitting port network kinetic equations and numerical, as a result, the error between the experimental results calculated by model and actual data is 4.95%, and the average prediction error during 2009-2013 is less than 2%, the fitting of parameters in this model needed to be supported by historical data, so this model is only applicable in short-term prediction with high accuracy.
Keywords :
complex networks; network theory (graphs); sea ports; traffic control; Tianjin Port; complex network structure; complex network system; forecasting model parameter; port network kinetic equation; port vessel traffic flow forecasting model; ports system; relevance rating; short-term prediction; vessel traffic flow prediction model; vessel traffic volume; weighted port evolutional network model; Complex networks; Forecasting; Mathematical model; Ports (Computers); Predictive models; Solid modeling; Transportation; complex network; port system; prediction model; vessel traffic flow;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Transportation Information and Safety (ICTIS), 2015 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4799-8693-4
Type :
conf
DOI :
10.1109/ICTIS.2015.7232104
Filename :
7232104
Link To Document :
بازگشت