k-means聚类分析算法在人工智能+个性化学习系统中的应用  

Application research of k-means cluster analysis algorithm in artificial intelligence+personalized learning system

作　　者：浦慧忠[1] PU Huizhong(Wuxi City College of Vocational Technology,Wuxi Jiangsu 214153,China)

机构地区：[1]无锡城市职业技术学院,江苏无锡214153

出　　处：《智能计算机与应用》2022年第8期152-156,共5页Intelligent Computer and Applications

基　　金：江苏省高校哲学社会科学研究项目(2020SJA0956)。

摘　　要：从个性化学习系统中学生成绩分析的需求现状出发,针对人工智能中经典算法k-means中初始点选择不合适导致的缺陷,同时考虑到个性化学习系统中学生成绩分析存在数据量大、数据类型复杂等现实问题,参考采用多次取样、一次聚类寻找最优解的改进算法,并通过模拟系统实验,验证了该算法的稳定性及应用效果。Starting from the current situation of the demand for student achievement analysis in the personalized learning system,aiming at the defects caused by the inappropriate selection of initial points in the classical algorithm k-means of artificial intelligence,and considering the large amount of data and complex data types in the analysis of student achievement in the personalized learning system,thereafter referring to the improved algorithm for finding the optimal solution such as multiple sampling and one clustering,the improved algorithm is used to find the optimal solution,and the stability and application effect of the algorithm are verified through simulation system experiments.

关 键 词：人工智能 聚类 K-MEANS算法 个性化学习 

分 类 号：TP392[自动化与计算机技术—计算机应用技术]