基于Minibatch-kMeans和XGBoost算法的大型场所WLAN室内定位的方法

WLAN Indoor Localization Method with Minibatch-KMeans and XGBoost

基于RSS的WLAN指纹定位算法,针对大型场所的室内定位数据维数高,计算量大,定位精度不高的问题,本文提出一种基于先聚类再分类的方法.本文用Minibatch-kMeans先聚类分区定位,然后采用XGBoost分类算法在子区域精确定位,解决了大型场所室内定位数据维数高,运算速度慢的问题,并提高了定位的精度。本文提出的算法具有很大的应用价值和应用前景。

Based on the WLAN fingerprint localization algorithm,this paper proposes a method based on pre-cluster classification algorithm,which is implemented by Minibatch-KMeans clustering and XGBoost classification algorithm.It solve the problem of large-scale data dimension,problem of slow operation speed and improved positioning accuracy.The algorithm proposed in this paper has great application value and prospects.