结果(博弈论)
点(几何)
人工神经网络
人工智能
计算机科学
研究对象
强化学习
机器学习
工程类
运筹学
数学
几何学
数理经济学
区域科学
地理
摘要
As the level of tennis improves, the ability and strategy to play in the game determine the responsibility for the outcome of the game. It is committed to improving the professional and strategic level of Asian tennis players and narrowing the gap with high-level European and American tennis players. The purpose of this paper is to study the application of machine learning in the study of the evaluation model of the technical and tactical effectiveness of tennis matches, and proposes the decision tree algorithm, artificial neural network, reinforcement learning algorithm, and related concepts of tennis matches. Therefore, this paper selects Federer’s technical and tactical games from 2013 to 2017 as the research object. And by paying attention to the application characteristics of Federer’s methods and strategies in each stage, a detailed statistical analysis of the data is carried out point by point. The exploratory outcomes show that through the AI calculation, it is found that the incredible skill and vital sufficiency of Federer’s hard court game change around 0.600, and the typical worth is 0.594. Particular and vital efficiency showed a sluggish recuperation in 2017.
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