突变数据融合在电力传感器网络中的应用
Application of Mutations Data Fusion in Power Sensor Network
顾成喜 1赵晓峰2
作者信息
- 1. 苏州市职业大学计算机工程学院,江苏苏州215104
- 2. 上海市南电力(集团)有限公司,上海201100
- 折叠
摘要
针对传统电力传感器网络下突变电力传感数据的融合方法无法将传感器节点发送的多个电力传感数据同时进行消除热备份融合处理,使电力传感器采集的信息不完整,存在较大弊端,提出了一种基于电力传感器下神经网络的电力传感数据融合模型.将电力传感器采集的电力传感数据信息划分簇层次结构与神经网络的层次结构相结合,设计一个多层电力传感数据融合感知模型,将以簇为单位的电力传感数据通过神经网络将突变电力传感数据发送给汇聚节点进行融合.仿真结果表明,基于电力传感器下神经网络的电力传感数据融合模型可以同时对传感器节点发送的多个电力传感数据进行消除热备份,达到电力传感器网络完整采集有效信息的目的.
Abstract
In view of the incomplete information acquisition by the power sensor due to the failure to eliminate simultaneously hot backup for fusion processing the multiple power sensor data transimitted from sensor nodes in the traditional mutations power sensor data fusion method.Therefore,this paper proposes a power sensor data fusion model based on the power sensor neural network.Divide the power sensor data information into cluster hierarchy to combine with the hierarchical structure of the neural network; design a multi-layer perception model for power sensor data fusion ; send mutation power sensor data via neural network to the sink nodes for fusion.The simulation results show that this proposed model can simultaneously eliminate hot backup of multiple power sensor data transimitted from sensor nodes.Thereby,the power sensor network can completely collect effective information.
关键词
传感器网络/突变电力传感数据/神经网络融合Key words
sensor network/mutations power sensor data/neural network fusion引用本文复制引用
基金项目
国家自然科学基金(61472268)
苏州市职业大学预研项目(2013SZDYY02)
苏州市科技支撑计划(SS201336)
出版年
2014
NETL
NSTL
维普
万方数据