Application of GM(1,1) Model Based on Residual Error Correction in Athletic Performance Prediction
Qing-bin Wang, Ling Jia
Available Online December 2015.
- https://doi.org/10.2991/icmmcce-15.2015.302How to use a DOI?
- Men’s 200m Race; GM(1,1) Model; Residual Error
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - https://doi.org/10.2991/icmmcce-15.2015.302 ID - Wang2015/12 ER -