DocumentCode
527527
Title
Notice of Retraction
Prediction of aerobics achievement basing on neural network
Author
Bai Kai-xiang ; Gaoming ; Yin Hang ; Cheng Yin ; Wang Ni
Author_Institution
Health Inst., Wuhan Inst. of Phys. Educ., Wuhan, China
Volume
1
fYear
2010
fDate
10-12 Aug. 2010
Firstpage
503
Lastpage
508
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.
In this paper, the methods of the clustering analysis and relationship analysis were applied to filtrate several main indicators correlating closely to specific performance from 32 indicators of the physical shape and quality, and then a non-linear mathematical model was established by the method of neural network between the specific performance and main indicators of physical shape and quality, which was utilized to predict accurately the specific performances of Aerobics´ athletes.
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.
In this paper, the methods of the clustering analysis and relationship analysis were applied to filtrate several main indicators correlating closely to specific performance from 32 indicators of the physical shape and quality, and then a non-linear mathematical model was established by the method of neural network between the specific performance and main indicators of physical shape and quality, which was utilized to predict accurately the specific performances of Aerobics´ athletes.
Keywords
data analysis; neural nets; pattern clustering; sport; aerobics achievement prediction; clustering analysis; neural network; nonlinear mathematical model; relationship analysis; Analytical models; Artificial neural networks; Correlation; Data models; Mathematical model; Predictive models; Shape; Aerobics achievement(AA); neural network (NN); physical shape and quality indicators(PSQI); prediction;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location
Yantai
Print_ISBN
978-1-4244-5958-2
Type
conf
DOI
10.1109/ICNC.2010.5583141
Filename
5583141
Link To Document