欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
为了解决节点分布密集环境中网络数据融合能耗较大的问题,提出了一种基于代理和熵权的分组融合算法。该算法首先通过节点监测数据相似度的对比,摒除组内故障节点的影响;然后采用C/S模式对组内节点进行融合,以组融合数据代替节点数据参与融合;最后采用代理模式对各组融合数据进行熵权融合。仿真结果证明该方案能以较小的能耗代价获取准确的融合结果,有效减少了网络延迟。
英文摘要：
To overcome the huge energy consumption of data fusion in the sensor network cause by nodes dense deployment,this paper proposed an agent and entropy weight-based group data fusion algorithm.The algorithm first excluded the failure nodes＇ effect by the similarity comparison of nodes＇ monitoring data.And then obtained the fusion data of nodes by the entropy weight fusion of nodes with the model of C/S in groups,using the fusion datas obtained by C/S model to replace the monitoring datas of nodes when performed next fusion process.At last,fusioned the fusion dates with the model of agent between groups.The simulation results show that the proposed algorithm can obtain the accurate data fusion result with a smaller energy cost,and effectively in reducing network latency.
同期刊论文项目
同项目期刊论文
Optimizing sphericallight-emitting diode array for highly uniform illumination distribution byemploy
A self-organization particle swarm optimization algorithm based on L norm multi-measurement diversit
A novel gravitationalacceleration enhanced particle swarm optimization algorithm for wind-thermaleco
A new design method foradaptive IIR system identification using hybrid particle swarm optimization a
Robust H-infinity guaranteed cost control for uncertain switched descriptor delayed systems with non
期刊信息
位置：