DocumentCode
1949363
Title
Notice of Retraction
Application of support vector regression in regional logistics requirement forecasting
Author
Yan Yue
Author_Institution
Coll. of Comput. Sci. & Inf. Eng., Chongqing Technol. & Bus. Univ., Chongqing, China
Volume
2
fYear
2010
fDate
9-11 July 2010
Firstpage
321
Lastpage
324
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.
Prediction of regional logistics requirement provides a basis for the plan of regional logistics. In the study, support vector regression is presented to predict regional logistics requirement. The regional logistics data from 1996 to 2006 in Shanghai municipality are used as the application data of support vector regression. The comparison of prediction error between BP neural network and support vector regression is applied to testify the superiority of support vector regression. The comparison results show that the prediction results of support vector regression are better than those of BP neural network.
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.
Prediction of regional logistics requirement provides a basis for the plan of regional logistics. In the study, support vector regression is presented to predict regional logistics requirement. The regional logistics data from 1996 to 2006 in Shanghai municipality are used as the application data of support vector regression. The comparison of prediction error between BP neural network and support vector regression is applied to testify the superiority of support vector regression. The comparison results show that the prediction results of support vector regression are better than those of BP neural network.
Keywords
backpropagation; forecasting theory; logistics; neural nets; regression analysis; support vector machines; BP neural network; Shanghai municipality; regional logistics requirement forecasting; support vector regression; Forecasting; Predictive models; Support vector machines; BP neural network; regional logistics; requirement forecasting; support vector regression;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-5537-9
Type
conf
DOI
10.1109/ICCSIT.2010.5564587
Filename
5564587
Link To Document