DocumentCode
1965886
Title
Notice of Retraction
An ensemble forecasting model for port throughput
Author
Lili Qu ; Yan Chen ; Shengjun Qin ; Shuyong Liu
Author_Institution
Transp. Manage. Sch., Dalian Maritime Univ., Dalian, China
Volume
2
fYear
2010
fDate
10-11 July 2010
Firstpage
117
Lastpage
120
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
To accurately forecast port throughput is crucial to the success of any port operation policy. This paper attempts to create an optimal ensemble predictive model of port throughput by using regression models, grey model and artificial neural network. Years of historical data (Jan. 2001 to Dec. 2009) from major ports in China mainland are collected and the data of Dalian Port is used to establish and validate a forecasting model. The empirical results show the effectiveness of the proposed ensemble forecasting model for port throughput prediction.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
To accurately forecast port throughput is crucial to the success of any port operation policy. This paper attempts to create an optimal ensemble predictive model of port throughput by using regression models, grey model and artificial neural network. Years of historical data (Jan. 2001 to Dec. 2009) from major ports in China mainland are collected and the data of Dalian Port is used to establish and validate a forecasting model. The empirical results show the effectiveness of the proposed ensemble forecasting model for port throughput prediction.
Keywords
economic forecasting; goods distribution; neural nets; production engineering computing; regression analysis; transportation; China mainland; Dalian Port; artificial neural network; ensemble forecasting model; grey model; port operation policy; port throughput; regression model; Biological system modeling; Forecasting; Predictive models; ANN; Port throughput; ensemble forecasting; grey model; regression model;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial and Information Systems (IIS), 2010 2nd International Conference on
Conference_Location
Dalian
Print_ISBN
978-1-4244-7860-6
Type
conf
DOI
10.1109/INDUSIS.2010.5565665
Filename
5565665
Link To Document