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Predict the neural network mathematical model of basketball team scores based on improved BP algorithm

机译:基于改进BP算法的篮球队得分神经网络数学模型预测

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Sports performance has increasingly become the measure and the symbol of a country???s economic strength, educational level, and comprehensive national strength. As one of the three big ball games, basketball also occupies a pivotal position in the national sport. In order to achieve better play results and provide a good guide for peacetime training and policy development, the study applies the improved BP neural network to establish the mathematical prediction model of the men???s basketball performance. Based on MATLAB mathematical software, according to the actual data as shooting rate, three-point shooting, assists statistics, rebounding, obtained from the 2004 Olympic Games, the 14th World Basketball Championships, the 2006 Intercontinental Cup basketball game and the 2004Athens Olympic Games, the 2012 London Olympic Games sports scores were predicted. The analysis of the predicted results and the actual results showed that the error is small; there is a theoretical feasibility of the algorithmin practical problems.After constantly improving and updating the internal data of the model, the model can provide better service for basketball development and can be applied to other areas.
机译:体育成绩已日益成为衡量一个国家经济实力,教育水平和综合国力的手段和象征。作为三大球类运动之一,篮球在民族运动中也占有举足轻重的地位。为了获得更好的比赛成绩并为平​​时训练和政策制定提供良好的指导,本研究应用改进的BP神经网络建立了男子篮球成绩的数学预测模型。基于MATLAB数学软件,根据从2004年奥运会,第14届世界篮球锦标赛,2006年洲际杯篮球比赛和2004年雅典奥运会获得的射门率,三分球,助攻统计,篮板等实际数据,对2012年伦敦奥运会的运动成绩进行了预测。对预测结果和实际结果的分析表明,误差很小。该算法在实际问题上具有理论上的可行性。在不断改进和更新模型的内部数据后,该模型可以为篮球的发展提供更好的服务,并可以应用于其他领域。

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