%0 Journal Article
%T Student status analysis system research based on hybrid clustering algorithm<br>基于杂交聚类算法的学生状态分析系统研究
%A XIAO Li-zhong
%A HU Ting
%A LIU Yun-xiang
%A LIN Zhen-jun
%A WU Yan-lin a
%A <br>肖立中
%A 胡婷
%A 刘云翔
%A 林振骏
%A 吴雁林a
%J 计算机应用研究
%D 2012
%I 
%X With the number of students and their information increasing, the original student management and evaluation pattern could not meet demand in college. This paper researched a student status analysis system, which could collect the students' comprehensive data and provide platform to communicate between counsellor and students. In view of the deficiency of global search ability for K-means clustering algorithm, this paper proposed K-means algorithm based on particle swarm optimization to analyze the students' data. Compared with those of K-means algorithm, K-means algorithm based on genetic algorithm and artificial evaluation, the results show the evaluation obtained from the system is more comprehensive and objective. The system could also offer visual information convenient to query, which helped counsellor find sticking point timely and improve efficiency.
%K student management
%K student status evaluation
%K particle swarm optimization algorithm
%K K-means algorithm<br>学生管理
%K 学生状态评估
%K 粒子群优化算法
%K K-均值算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=AB480754FB5F26FEA917EC5845D74343&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=B31275AF3241DB2D&sid=BF8433C728988BC0&eid=64CEB0152F392142&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=10