DocumentCode
518442
Title
Notice of Retraction
Analysis and forecasting model of tourism economy based on improved support vector regression
Author
Liu Taian ; Xue Xin ; Wei Guangcun ; Shen Chuanhe ; Liu Xinying
Author_Institution
Dept. of Inf. & Eng., Shandong Univ. of Sci. & Technol. (SDUST), Taian, China
Volume
1
fYear
2010
fDate
16-18 April 2010
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.
This paper analyses the correlation of the data indicators of tourism economy resources firstly. Because there are higher nonlinear and larger volatility with the analysis and forecasting of tourism economy, this paper gives the analysis and forecasting model of tourism economy based on improved support vector regression (SVR) secondly. All kinds of kernel function are used in the numerical test based on the tourism economy data of Taian from January 2000 to December 2008 lastly. The numerical test results show that the improved SVR model of tourism economy forecasting is effective.
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.
This paper analyses the correlation of the data indicators of tourism economy resources firstly. Because there are higher nonlinear and larger volatility with the analysis and forecasting of tourism economy, this paper gives the analysis and forecasting model of tourism economy based on improved support vector regression (SVR) secondly. All kinds of kernel function are used in the numerical test based on the tourism economy data of Taian from January 2000 to December 2008 lastly. The numerical test results show that the improved SVR model of tourism economy forecasting is effective.
Keywords
economics; forecasting theory; numerical analysis; support vector machines; travel industry; data indicators; forecasting model; improved support vector regression; kernel function; tourism economy resources; Algorithm design and analysis; Data engineering; Economic forecasting; Information analysis; Kernel; Mathematical model; Predictive models; Support vector machines; Technology forecasting; Testing; forecasting model; kernel function; support vector regression; tourism economy data indicators;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-6347-3
Type
conf
DOI
10.1109/ICCET.2010.5486205
Filename
5486205
Link To Document