计算机应用与软件2016，Vol.33Issue(6)：114-117,4.DOI:10.3969/j.issn.1000-386x.2016.06.028
基于改进BP神经网络的室内无线定位方法
INDOOR WIRELESS POSITIONING BASED ON IMPROVED BP NEURAL NETWORK
摘要
Abstract
For indoor wireless positioning,we used an improved BP neural network to overcome the low accuracy and signal instability when a weighted centroid positioning method being adopted.We established the BP network structure by using the received signal strength indication (RSSI)as input and the two-dimensional position as output.The mind evolutionary computation was used to optimise its initial weights and thresholds.The network was trained by 196 sample data within a square area of 3 m side length.Experimental results showed that it was able to achieve the positioning accuracy by 0.1 m at 27 predictive test points.Compared with a standard BP neural network as well as with a combination of BP network and genetic algorithm,this positioning method had the performance of short training and convergence time, the positioning result was stable as well.关键词
室内定位/BP神经网络/思维进化算法/接收信号强度指示Key words
Indoor positioning/BP neural network/Mind evolutionary computation (MEC)/Received signal strength indicator分类
信息技术与安全科学引用本文复制引用
刘晓晨,张静..基于改进BP神经网络的室内无线定位方法[J].计算机应用与软件,2016,33(6):114-117,4.基金项目
国家自然科学基金项目（61101209）；上海市自然科学基金项目（11ZR1426600）；上海师范大学一般科研项目（DYL201406）；上海师范大学重点学科基金项目（DZL126）。 （）
