基于人工免疫聚类算法的电梯交通流分析  

Elevator Traffic Flow Analysis Based on Artificial Immune Clustering Algorithm

作　　者：李中华[1] 朱燕飞[1] 李春华[1] 毛宗源[1] 

机构地区：[1]华南理工大学自动化科学与工程学院,广东广州510640

出　　处：《华南理工大学学报（自然科学版）》2003年第12期26-29,共4页Journal of South China University of Technology(Natural Science Edition)

摘　　要：采用人工免疫聚类算法对某大楼一周内的电梯交通流进行了分析 .利用人工免疫算法的免疫激励和免疫抑制机制 ,对电梯交通的 5分钟原始客流数据进行压缩 ,得到了特点鲜明的电梯交通流人工免疫记忆数据集 .以最小支撑树为工具 ,采用最短距离法对记忆数据集进行分类 ,所得结果清晰地体现了电梯交通流的实际特性 .By employing an artificial immune clustering algorithm, the elevator traffic flow in a certain building during one week was analyzed. The promotion and suppression mechanisms of artificial immune algorithm were exploited to compress the original elevator traffic flow data collected in 5 min, and a distinct elevator traffic flow memory dataset was obtained. The memory dataset was then classified on the basis of two methods: the Minimal Spanning Tree and the Minimal Distance Method. The result of classification clearly reveals the real feature of elevator traffic. Therefore, the approach addressed here may provide a powerful theoretical support for elevator group control.

关 键 词：人工免疫系统 聚类分析 电梯交通流 电梯群控算法 

分 类 号：TU857[建筑科学] TP274[自动化与计算机技术—检测技术与自动化装置]