复杂网络数据信息传输稳定性检测仿真研究
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摘要
对复杂网络数据信息传输的稳定性检测,能够有效保障网络的稳定运行。对信息传输稳定性的检测,需要获取各个数据对象与其邻域的加权距离,计算出每个数据对象的离群度量值,完成对数据信息传输稳定性的检测。传统方法计算出数据集的属性个数,获取每条数据记录的离群度,但忽略了计算出每个数据对象的离群度量值,导致检测精度偏低。提出基于密度的复杂网络数据信息传输稳定性检测方法。将网络整体的数据分布状态划分为不同类型的区间,描述网络信息组,对网络各个区域的数据流密度进行划分,给出稠密网格的区域,利用空间属性及其空间关系确定不同数据密度空间邻域,获取各个数据对象与其邻域的加权距离,计算出每个数据对象的离群度量值,完成对复杂网络数据信息传输稳定性检测。仿真证明,所提方法数据检测精度高,为提升和保障网络的稳定运行奠定了基础。
A stability detection method for data information transmission of complex networks is proposed based on density.Firstly,the holistic data distribution of the network is divided into different types of intervals,and the network information group is described,and then the data flow density of each region of the network is partitioned to dense grid regions.Secondly,spatial attributes and their spatial relations are utilized to determine the spatial neighborhood of different data densities to obtain weighted distance between each data object and its neighborhood.Finally,the outlier metric of each data object is calculated to complete the stability detection for data information transmission of complex networks.The simulation results show that the method has high detection accuracy.It can promote and guarantee stable operation of network.
A stability detection method for data information transmission of complex networks is proposed based on density.Firstly,the holistic data distribution of the network is divided into different types of intervals,and the network information group is described,and then the data flow density of each region of the network is partitioned to dense grid regions.Secondly,spatial attributes and their spatial relations are utilized to determine the spatial neighborhood of different data densities to obtain weighted distance between each data object and its neighborhood.Finally,the outlier metric of each data object is calculated to complete the stability detection for data information transmission of complex networks.The simulation results show that the method has high detection accuracy.It can promote and guarantee stable operation of network.
引文
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[2]李海林,郭崇慧.时间序列数据挖掘中特征表示与相似性度量研究综述[J].计算机应用研究,2013,30(5):1285-1291.
[3]贾伟.物联网的数据采集与信息传输技术研究[J].现代电子技术,2016,39(5):33-37.
[4]朱利鹏,等.基于数据挖掘的区域暂态电压稳定评估[J].电网技术,2015,39(4):1026-1032.
[5]黄斌,许舒人,蒲卫.基于MapReduce的数据挖掘平台设计与实现[J].计算机工程与设计,2013,34(2):495-501.
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[7]王叶南,陈江华.远距离温度信息传输稳定性研究[J].自动化仪表,2015,36(7):88-89.
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