煤炭工程 ›› 2013, Vol. 45 ›› Issue (11): 129-131.doi: 10.11799/ce201311043

• 信息工程 • 上一篇    下一篇

基于人工鱼群算法煤矿井下人员定位技术研究

徐善永1,黄友锐1,曲立国2   

  1. 1. 安徽理工大学电气与信息工程学院
    2. 安徽理工大学
  • 收稿日期:2013-08-16 修回日期:2013-09-25 出版日期:2013-11-10 发布日期:2013-11-11
  • 通讯作者: 徐善永 E-mail:xsyong326@163.com

Study of positioning technology of Underground Coal Mines based on Artificial Fish-Swarm Algorithm

  • Received:2013-08-16 Revised:2013-09-25 Online:2013-11-10 Published:2013-11-11

摘要:

为了进一步提高煤矿井下人员、设备定位的精确性,文章提出将RSSI节点定位算法和人工鱼群算法相结合,利用基于距离的质心算法构造初始种群,通过迭代寻优,提高节点的定位精度。仿真实验结果表明,该算法提高了井下网络节点的定位精度。

关键词: 无线传感网络, 节点定位, 距离式质心算法, 人工鱼群算法

Abstract:

In order to further improve positioning accuracy of coal mine staff, equipment, articles submitted to RSSI localization algorithm combined with artificial fish-swarm algorithm using centroid algorithm based on distance of the initial population, through iterative optimization, improve positioning accuracy of a node. Simulation results show that the algorithm improves the positioning accuracy of underground network nodes.

Key words: Wireless Sensor Networks, Node localization, Distance-centroid algorithm, artificial fish-swarm

中图分类号: