传感技术学报2011，Vol.24Issue(1)：122-127,6.DOI:10.3969/j.issn.1004-1699.2011.01.025
基于神经网络的无线传感器网络数据融合算法
Data Aggregation of Wireless Sensor Networks Using Artificial Neural Networks
摘要
Abstract
To reduce communication traffic and save energy for wireless sensor networks ( WSNs), BPNDA, a data aggregation algorithm based on back-propagation networks, was proposed, which integrates a three-layer BP neural network with clustering routing protocol. The input layer neuron is located in cluster members, while the hidden layer neuron and the output layer neuron are located in cluster head. Only the processed data represented the features of the raw collected data will be transmitted to the sink, so the efficiency of data gathering is improved and the lifetime of the network is prolonged. Simulation results show that compared with LEACH ,the BPNDA algorithm effectively reduced the data traffic and decreased the energy dissipated of nodes.关键词
无线传感器网络/数据融合/神经网络/分簇Key words
wireless sensor networks/ data aggregation/ artificial neural networks/ cluster分类
信息技术与安全科学引用本文复制引用
孙凌逸,黄先祥,蔡伟,夏梅尼..基于神经网络的无线传感器网络数据融合算法[J].传感技术学报,2011,24(1):122-127,6.基金项目
军事单位资助项目 （）
