窦小磊, 王佳欣. 组合网络最优决策控制拓扑建模与结构鲁棒性分析[J]. 微电子学与计算机, 2015, 32(5): 126-129. DOI: 10.19304/j.cnki.issn1000-7180.2015.05.026
引用本文: 窦小磊, 王佳欣. 组合网络最优决策控制拓扑建模与结构鲁棒性分析[J]. 微电子学与计算机, 2015, 32(5): 126-129. DOI: 10.19304/j.cnki.issn1000-7180.2015.05.026
DOU Xiao-lei, WANG Jia-xin. Strong Motion Railway Communication Signal Environment Accurately Collect Research and Simulation Method[J]. Microelectronics & Computer, 2015, 32(5): 126-129. DOI: 10.19304/j.cnki.issn1000-7180.2015.05.026
Citation: DOU Xiao-lei, WANG Jia-xin. Strong Motion Railway Communication Signal Environment Accurately Collect Research and Simulation Method[J]. Microelectronics & Computer, 2015, 32(5): 126-129. DOI: 10.19304/j.cnki.issn1000-7180.2015.05.026

组合网络最优决策控制拓扑建模与结构鲁棒性分析

Strong Motion Railway Communication Signal Environment Accurately Collect Research and Simulation Method

  • 摘要: 提出组合网络最优决策控制拓扑建模与结构鲁棒性分析,通过筛选组合网络中控制结构鲁棒性影响因素,建立鲁棒性影响因素数据集合,并对组合网络获取最优决策控制,进行决策数据的安全性及性能分析,对组合网络的拓扑建模及鲁棒性进行准确的分析.仿真实验表明,组合网络最优决策控制拓扑建模与结构鲁棒性分析能够有效地提高组合网络控制的抗干扰能力及鲁棒性分析的准确性,并且在长时间运行过程中网络结构更加稳定,可靠性强,满足组合网络应用的实际需求.

     

    Abstract: Put forward combination structure of network topology modeling and optimal decision control robustness analysis, through the screening of Bernoulli node in the network robustness control structure influencing factors, establish robust factors affecting the data collection, and the combination of network to obtain the optimal decision control, decision-making data security and performance analysis, the combination of network topology modeling and robustness for the accurate analysis of the process. The simulation experiments show that the combination structure of network topology modeling and optimal decision control robustness analysis can effectively improve the anti-interference ability of combination network control accuracy and robustness analysis, and the network structure in the process of long running more stable and strong reliability. Meet the actual demand of combination of network application.

     

/

返回文章
返回