| 免疫规划K-均值聚类算法识别电梯群控交通流模式 |
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| 引用本文： | 唐桂忠,张广明,朱炜.免疫规划K-均值聚类算法识别电梯群控交通流模式[J].计算机测量与控制,2005,13(9):938-940. |
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| 作者姓名： | 唐桂忠 张广明 朱炜 |
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| 作者单位： | 南京工业大学,自动化学院,江苏,南京,210009 |
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| 基金项目： | 江苏省教育基金资助项目(03KJB510043) |
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| 摘 要： | 提出了一种基于免疫规划K-均值聚类算法的电梯交通流模式识别新方法,以该系统前7 d的交通流数据为样本,采用免疫k-均值算法对其进行聚类分析,产生的类别对应交通流模式,将实时采样数据划分到交通流模式对应的类中,能够识别25种交通流模式;实验表明该方法识别电梯交通流模式正确率高,可以指导系统优化派梯策略,算法的收敛速度较快,能够满足群控系统的实时性要求.
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| 关 键 词： | K-均值 免疫聚类算法 电梯群控 交通流模式 |
| 文章编号： | 1671-4598(2005)09-0938-03 |
| 修稿时间： | 2005年1月11日 |
Traffic Pattern Identification of Elevator Group Control System Based on Immune Evolutionary K-means Clustering Algorithm |
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| Tang Guizhong,Zhang Guangming,Zhu Wei.Traffic Pattern Identification of Elevator Group Control System Based on Immune Evolutionary K-means Clustering Algorithm[J].Computer Measurement & Control,2005,13(9):938-940. |
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| Authors: | Tang Guizhong Zhang Guangming Zhu Wei |
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| Abstract: | A new method of traffic pattern identification for elevator group control system based on immune evolutionary k-means clustering algorithm is presented.In this algorithm,the traffic flow data of the first seven days of this system is used as the sample and the data characteristic of primitive traffic flow is obtained.The current traffic flow data will be divided to the corresponding traffic pattern and recognize 25 kinds of traffic flow modes. The result of experiment indicated that the correct rate of this way is relatively high.So this method can instruct the system to optimize dispatch strategy and improve the service performance of the elevator group.The convergence speed of this algorithm is fast,thereby satisfying the real time control of elevator group control system. |
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| Keywords: | K-means immune clustering algorithm elevator group control system traffic pattern |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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