cs.AI updates on arXiv.org 10月01日
NBA球员老化趋势分析及预测方法研究
index_new5.html
../../../zaker_core/zaker_tpl_static/wap/tpl_guoji1.html

 

本文探讨了NBA球员老化对表现的影响,运用自动编码器和K-means聚类机器学习方法对球员职业生涯趋势进行分类,并采用LSTM深度学习方法预测球员表现。研究数据来源于资深NBA球员的比赛数据,所提出的方法在评估不同类型NBA职业生涯趋势方面优于其他方法,具有泛化能力,可应用于体育分析领域的不同类型运动。

arXiv:2509.25858v1 Announce Type: new Abstract: The topic of aging decline on performance of NBA players has been discussed in this study. The autoencoder with K-means clustering machine learning method was adopted to career trend classification of NBA players, and the LSTM deep learning method was adopted in performance prediction of each NBA player. The dataset was collected from the basketball game data of veteran NBA players. The contribution of the work performed better than the other methods with generalization ability for evaluating various types of NBA career trend, and can be applied in different types of sports in the field of sport analytics.

Fish AI Reader

Fish AI Reader

AI辅助创作,多种专业模板,深度分析,高质量内容生成。从观点提取到深度思考,FishAI为您提供全方位的创作支持。新版本引入自定义参数,让您的创作更加个性化和精准。

FishAI

FishAI

鱼阅,AI 时代的下一个智能信息助手,助你摆脱信息焦虑

联系邮箱 441953276@qq.com

相关标签

NBA球员老化 机器学习 深度学习 职业生涯趋势 体育分析
相关文章