余振宝,卢小平,刘英,余培冬,张冬梅

• 1:河南理工大学自然资源部矿山时空信息与生态修复重点实验室
• 2:山东科技大学测绘科学与工程学院

摘要(Abstract)：

针对传统路径损耗模型测距过多依赖于环境参数A和n的问题,该文在分析BP神经网络模型的基础上,引进了基于蚁群算法优化BP神经网络模型(ACO-BP)的信号衰减模型。利用蚁群算法寻找最优的初始阈值和权值,并将其赋予BP神经网络;将信号强度作为输入值,距离作为输出值对ACO-BP网络进行训练;利用Matlab进行模拟仿真实验。实验结果表明:ACO-BP神经网络比BP神经网络预测距离值的精度平均提高了75%,该算法可应用于无线网络室内定位技术中。

关键词(KeyWords)： 路径损耗模型;ACO-BP神经网络;RSSI;室内定位

Abstract:

Keywords:

基金项目(Foundation): 2016年国家重点研发计划项目(2016YFC0803103);; 河南省高校创新团队支持计划项目(14IRTSTHN026)

作者(Author): 余振宝,卢小平,刘英,余培冬,张冬梅

DOI: 10.16251/j.cnki.1009-2307.2020.11.008

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