In the field of martial arts, athletes can win the initiative in the competition if they can correctly and timely acquire the field knowledge, evaluate the situation efficiently, and formulate a suitable strategy. In this paper, we use fuzzy mathematics, mathematical statistics, and artificial intelligence learning algorithms to carry out systematic and in-depth research on the selection of Wushu competition scene decision-making. The fuzzy mathematics theory is combined with the intelligent design theory for decision-making based on a multiagent, case-based reasoning selection, and adaptability evaluation analysis. The Wushu competition scene decision system is constructed based on artificial intelligence learning algorithms. Our approach outperforms the existing approaches in terms of accuracy, sensitivity, specificity, and Matthew’s correlation coefficient (MCC). The results of our proposed model can be anticipated to have the potential for better flexibility and scalability in martial arts competition.

中文翻译：

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基于深度学习的武术比赛智能决策系统

在武术领域，如果运动员能够正确，及时地获得田野知识，有效地评估情况并制定合适的策略，则可以赢得比赛的主动权。本文运用模糊数学，数理统计和人工智能学习算法对武术比赛场景决策的选择进行系统，深入的研究。模糊数学理论与智能设计理论相结合，用于基于多主体的决策，基于案例的推理选择和适应性评估分析。武术比赛场景决策系统是基于人工智能学习算法构建的。我们的方法在准确性，敏感性，特异性，和Matthew的相关系数（MCC）。我们提出的模型的结果可以预期在武术比赛中具有更好的灵活性和可扩展性的潜力。