A Novel prediction model for champions’ scores of men’s 110 - meter hurdle in Olympic Games

Xiaoxin Li

COMPUTER MODELLING & NEW TECHNOLOGIES 2013 17(5C) 34-37

School of Physical Education, China University of Mining and Technology, Xuzhou, Jiangsu Province, 221116

In order to improve the prediction accuracy of the grey model for champions’ scores of men’s 110-meter hurdle in Olympic Games, a nonlinear grey Bernoulli model (NGBM) has been built on the base of the GM(1, 1) model, and a genetic algorithm (GA) has been adopted to optimize the parameters of the model. Based on the statistics of champions’ scores of men’s 110-meter hurdle in Olympic Games during the 1948 - 2012 period, the NGBMGA model is employed to predict the performance of the 2016 and 2020 Olympic Games which is contrasted against the prediction result of the GM (1, 1) model. The results show that the NGBMGA model has higher prediction accuracy, with its feasibility and veracity verified.