摘要
针对影响体育比赛成绩的因素很多,传统的体育预测方法很难得到满意预测结果的现状。利用跳远运动员专项成绩与素质训练水平之间的相关关系,借助BP神经网络强大的非线性映射能力,提出了跳远运动员专项成绩的神经网络预测模型。该模型弥补了传统预测方法的不足,充分利用了数据中所包含的信息,与传统的预测方法相比,预测结果的精确度有了较大的提高。为解决该领域内复杂的难以用传统数学方法解决的问题提供了一种新颖的思路和方法。从而为运动员进行科学训练提供了理论依据。
The factors influencing the sports scores are a lot. The traditional sports predicted method is difficult to obtain satisfactory. results. According to the correlation between specific performance and quality training level of long jumper, based on the powerful nonlinear mapping ability of BP neural network, the paper builds the neural network model of long jumper＇s specific performance. The model makes up for the deficiency of traditional forecasting methods, and makes full use of the information contained in the data, and compared with the traditional prediction method, the accuracy of the prediction results have greatly improved. The paper puts forward a new thought and method to solve the problems that is difficult to solve by using traditional mathematical methods, providing a theoretical basis for scientifi~ training for athletes.
出处
《价值工程》
2013年第3期178-180,共3页
Value Engineering
关键词
BP神经网络
跳远运动员
专项成绩
预测精度
BP neural network
long jump athletes
special scores
prediction accuracy
