基于群体智能聚类算法的电梯交通流分析

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

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 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.