南京理工大学学报（自然科学版）2017，Vol.41Issue(4)：428-433,6.DOI:10.14177/j.cnki.32-1397n.2017.41.04.005
和声搜索算法优化神经网络的无线网络室内定位
Indoor positioning of wireless network based on harmonysearch algorithm optimizing neural network
摘要
Abstract
Indoor environment is complex and changeable,and wireless signal has strong time-varying.Support vector machine has low positioning efficiency while neural network is difficult to determine the parameter.In order to improve the positioning performance in wireless network,a novel wireless positioning algorithm based on harmony search algorithm optimizing neural network is proposed.Firstly,training samples of wireless network are collected and the size of training samples is reduced by a compressed sensing algorithm;secondly,clustering algorithm is used to cluster the samples;finally,harmony search algorithm is used to optimize neural network and feasibility is tested by simulation experiments.Test results show that the positioning results of the proposed algorithm can meet the actual requirements of wireless network positioning.关键词
无线网络室内定位/压缩感知算法/训练样本/聚类分析/和声搜索算法/神经网络Key words
wireless indoor positioning/compressed sensing algorithm/training samples/mean clustering analysis/harmony search algorithm/neural network分类
信息技术与安全科学引用本文复制引用
付思源,王华东..和声搜索算法优化神经网络的无线网络室内定位[J].南京理工大学学报（自然科学版）,2017,41(4):428-433,6.基金项目
国家自然科学基金(U1504613) （U1504613）
河南省高校科技创新团队计划(17IRTSTHN009) （17IRTSTHN009）
