基于群体智能聚类算法的电梯交通流分析

提出了一种基于群体智能的电梯交通流分析方法，该算法将电梯交通流模式投影于二维平面上，然后依据群体智能聚类，实现电梯交通流的自组织聚类分析．为了提高群体智能聚类算法的运行效率，采用了主成分分析方法改善模式投影时的随机性，同时在聚类过程中引入密度引导策略减小分类错误率和运行时间．仿真结果表明，群体智能聚类算法能对电梯交通流数据进行有效的聚类分析，具有较好的自组织聚类特性．

An algorithm for elevator traffic flow analysis based on swarm intelligence clustering

An algorithm for elevator traffic flow analysis based on swarm intelligence cluste- ring was proposed. Firstly, the elevator traffic flow data are mapped into a plane, and then analyzed by the clustering algorithm based on the swarm intelligence. To improve the run- ning efficiency of the algorithm, principal component analysis was utilized to reduce the mapping randomicity of elevator traffic flow data, and a density guiding policy was intro- duced to reduce the classification error rate and running time during clustering process. Sim- ulation shows that the proposed method can cluster the elevator traffic flow data effectively with good self-organizing characters.