基于一维卷积神经网络的CBA比赛结果预测  

CBA Games Result Prediction Based on One-dimensional Convolutional Neural Network

作　　者：文鹏 袁小艳[2] 韩梦姣 熊滔涛 向昕雨 WEN Peng;YUAN Xiaoyan;HAN Mengjiao;XIONG Taotao;XIANG Xinyu(School of Physical Education,Sichuan University of Arts and Science,Dazhou 635002,China;School of Artificial Intelligence and Big Data,Sichuan University of Arts and Science,Dazhou 635002,China)

机构地区：[1]四川文理学院体育学院,四川达州635002 [2]四川文理学院人工智能与大数据学院,四川达州635002

出　　处：《微型电脑应用》2024年第12期161-164,共4页Microcomputer Applications

摘　　要：篮球作为具有强对抗性的体育项目,其比赛结果对球队和观众都十分重要,同时也对体育博彩业有着较大影响,因此比赛结果的预测成了赛事外关注的重点之一。利用机器学习和深度学习对比赛结果进行预测,提出基于一维卷积神经网络(ID-CNN)的中国男子篮球职业联赛(CBA)比赛结果预测方法,将收集的CBA 2017—2022年5个赛季20支球队常规赛赛场数据进行皮尔逊相关系数计算和主成分分析(PCA)降维后,输入自建的ST-1D-CNN模型进行训练,实现对比赛结果的预测,模型达到了76.50%的准确率。As a competitive sport,results of the basketball game is so important to the team and the spectators,and has such an impact on the sports betting,so that predicting the results of the game becomes one of the main focuses of attention outside of the event.Machine learning and deep learning are used to predict the results of the game,this paper proposes a method for predicting the results of CBA games based on one-dimensional convolutional neural network,after the Pearson correlation coefficient calculation and principle component analysis(PCA)dimensionality reduction,the regular season data of 20 teams in the past 5 seasons of the CBA are input into the self-built ST-1D-CNN model for training to achieve the prediction of the results of the games,and the model reaches an accuracy rate of 76.50%.

关 键 词：篮球 一维卷积神经网络 皮尔逊相关系数 主成分分析 比赛结果预测 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]