基于GIS和人工神经网络的井下无线传感器网络定位数据修正方法研究

 针对传感器节点在自身定位过程中，受煤矿井下巷道复杂环境因素的影响，导致定位结果不够精确的问题，利用GIS系统的地图管理功能和人工神经网络（Artificial Neural Network）无需建立数学模型的特点，提出了GIS—ANN修正方法。实验结果表明：该方法对存在误差的节点坐标进行了有效的修正，从而提高了节点自身定位的精度。

Localization data correction of coal mine underground wireless sensor networks based on GIS and artificial neural network

Aiming at the problem of the positioning result of sensor node is not as accurate, by the complex environment factors of underground coal mine roadway, a GIS-ANN correction method was proposed. The method utilized map management functions of GIS system and the characteristic that is instead of having to establish the mathematical model of Artificial Neural Network. Experimental results show that the method effectively fixed the error of the node coordinates, so as to improve the accuracy of the node positioning itself.