Application of GM(1,1) Model Based on Residual Error Correction in Athletic Performance Prediction

DOI

10.2991/icmmcce-15.2015.302How to use a DOI?

Keywords

Men’s 200m Race; GM(1,1) Model; Residual Error

Abstract

In allusion to such problems in the athletic performance prediction as “poor information”, “small sample” and “dynamics” difficult to solve through traditional statistical methods, the application of the grey model will more effectively and accurately solve the above problems. However, the application of the grey model in the athletic performance prediction also encounters many problems, for example: the traditional GM(1,1) model cannot obtain corresponding accuracy in many prediction problems. The application of GM(1,1) grey model based on residual error correction in the athletic performance prediction is researched in this article. Specifically, the best performances of the world men’s 200m races during 2003~2013 are taken as the samples; then, GM(1,1) grey model based on residual error correction is adopted for sample modeling, wherein the prediction accuracy level of the model is the first level; then, the model obtained thereby is adopted for predicting the best performances of the world men’s 200m race in 2014, and the predicted performance is 20.59s.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Qing-bin Wang
AU  - Ling Jia
PY  - 2015/12
DA  - 2015/12
TI  - Application of GM(1,1) Model Based on Residual Error Correction in Athletic Performance Prediction
BT  - Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmcce-15.2015.302
DO  - 10.2991/icmmcce-15.2015.302
ID  - Wang2015/12
ER  -