基于人工鱼群算法的乒乓球数据挖掘  

Data Mining of Table Tennis Based on Artificial Fish Swarm Algorithm

作　　者：孟宪明[1] 凌培亮[1] 

机构地区：[1]同济大学机械工程学院,上海200092

出　　处：《计算机工程》2010年第5期28-31,共4页Computer Engineering

基　　金："十一五"国家科技支撑计划基金资助项目(2006BAK12B03);上海市自然科学基金资助项目(06ZR14153)

摘　　要：从视野和步长等方面对人工鱼群算法进行改进,结合乒乓球技战术的特点,对乒乓球技战术原始数据进行预处理。建立基于改进人工鱼群算法的乒乓球技战术分类规则数据挖掘模型,分析顶级乒乓球运动员比赛实例,结果表明与乒乓球技战术关联规则数据挖掘相比,该模型在挖掘质量和挖掘效果上有较大的优势。This paper improves the Artificial Fish Swarm Algorithm（AFSA） by modifying the strategies such as the field of vision and step in. Combining with the characteristics of table tennis technique and tactic, it adopts pre-processing on table tennis technique and tactic original data. The classification rule data mining model of table tennis technique and tactic based on improved AFSA is established. The match instances of top athletes are analyzed and the results show that compared with association rule data mining of the table tennis technique and tactic, this model has great advantage of rnining quality and mining effect.

关 键 词：人工鱼群算法 数据挖掘 分类问题 乒乓球 技战术 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]