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无线传感器是一种新兴的数据采集技术,为了消除传感器的数据之间冗余,加快通信的速度,提出一种灰色神经网络的传感器数据融合方法。首先对当前无线传感器数据融合的研究进行分析,然后采用多个传感器进行数据实时采集,并采用灰色模型和神经网络对传感器数据进行融合处理,有效去除重复的数据,可以用少量数据反映原始数据特征,最后在NS-2仿真平台上进行验证性。结果表明,本文方法降低传感器节点的通信能耗,降低了数据信息传送量,从而延长了无线传感器网络的寿命。
Wireless sensor is a new kind of data acquisition technology. In order to eliminate the redundancy between the sensor data and speed up the communication, a sensor data fusion method based on gray neural network is proposed. Firstly, the current wireless sensor data fusion research is analyzed. Then multiple sensors are used to collect the data in real time. The gray model and neural network are used to fuse the sensor data, so as to effectively remove duplicate data and reflect the original data features with a small amount of data , And finally verify the NS-2 simulation platform. The results show that this method can reduce the communication energy consumption of sensor nodes, reduce the data transmission, and extend the life of wireless sensor networks.