一种基于粒子群K均值聚类算法的电梯交通模式识别方法 PSO

代码说明：

  一种基于粒子群K均值聚类算法的电梯交通模式识别方法。该方法通过对此前一周的原始客流数据进行聚类分析，得到相应交通模式的聚类中心坐标[2]。针对实时变化的交通流数据，采集5 mins时段客流数据，根据最近邻原则划分其归属的聚类中心，从而识别出当前的交通模式。(Particle swarm-based K-means clustering algorithm Elevator Traffic Pattern Recognition. This method is through the previous week, data from the original cluster analysis of passenger traffic, the traffic patterns corresponding coordinates of cluster centers [2]. Changes in traffic flow for real-time data acquisition 5 mins time passenger flow data, according to the principle of division of its nearest neighbor cluster centers belonging to identify the current traffic patterns.)

文件列表：

PSO
...\calobjvalue.asv
...\calobjvalue.m
...\hs_err_pid476.log
...\initpop.asv
...\initpop.m
...\main.asv
...\main.m
...\regulate.asv
...\renew.asv
...\renew.m
...\untitled1.fig
...\老程序.txt