基于免疫无监督分类的老年人行为分析  

Elderly behavior analysis based on immune unsupervised classification

作　　者：孔令富[1] 李海涛[1] 

机构地区：[1]燕山大学信息科学与工程学院,河北秦皇岛066004

出　　处：《吉林大学学报（工学版）》2011年第6期1699-1703,共5页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家自然科学基金项目(60975062);河北省自然科学基金项目(F2010001295)

摘　　要：在建立行为特征量化模型的基础上,提出了无监督分类算法对日常行为规律进行分析和表示,并利用免疫原理对分类进行优化和改进。对比实验表明,该方法有效地克服了传统聚类方法的收敛速度慢和极值点等问题,实现了较好的分类效果。Based on the characteristic quantification models of behavior, an unsupervised classification algorithm was used to analyze and describe the daily pattern of the elderly behavior. Based on the immune principle the classification method was optimized and improved. Results of contrast experiments show that the proposed traditional clustering method, such as classification rate. method is effective to overcome the shortcomings slow convergence and extreme points, realizing a of the betterclassification rate.

关 键 词：人工智能 行为分析 免疫 无监督分类 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]