节点攻击策略下的军事通信网络结构优化算法  被引量:7

Optimization algorithm of military communication network structure under node attack strategy

在线阅读下载全文

作  者:杨芷柔 张虎 刘静 刘同林 YANG Zhirou;ZHANG Hu;LIU Jing;LIU Tonglin(School of Artificial Intelligence, Xidian University, Xi’an 710071, China;Beijing Electro-mechanical Engineering Institute, Beijing 100074, China)

机构地区:[1]西安电子科技大学人工智能学院,陕西西安710071 [2]北京机电工程研究所,北京100074

出  处:《系统工程与电子技术》2021年第7期1848-1855,共8页Systems Engineering and Electronics

基  金:国家自然科学基金(61703382);国防基础科研项目(JCKY2019204A007)资助课题。

摘  要:合理的军事通信网络结构能够充分利用信息优势达到制胜的目的,因此优化军事通信网络结构至关重要。首先,基于复杂网络理论并结合军事通信网络的拓扑结构特征建立了相应的网络结构模型,将侦查探测、火力打击和指挥控制实体抽象为节点,实体间复杂的连接关系抽象为边。在此基础上,以提升网络鲁棒性为目标,提出了一种基于进化思想的优化算法并对节点攻击策略下的军事通信网络结构进行优化研究,对比分析了不同优化算法下网络结构模型对鲁棒性的影响规律。仿真结果验证了网络模型和进化优化算法的有效性,对于深入研究军事通信网络建模和结构优化问题具有一定的借鉴意义。The reasonable military communication network structure could make full use of information to achieve the goal of winning.Therefore,it is important to optimize the structure of military communication networks.Firstly,corresponding network structure model is established based on complex network theory and the topological structure characteristics of military communication networks.The reconnaissance dection,fire entities and command and control entities in the system are abstracted as nodes,and the interactions between entities are abstracted as links.Then,in order to improve network robustness,an evolutionary algorithm is proposed to optimize the topology structure of military communication networks.Finally,several comparison algorithms are adopted to analyze the influence of network structure model on robustness.Experimental results show the validity of the network model and the evolutionary optimization algorithm,which is useful for reference in the study of military communication network modeling and structure optimization.

关 键 词:军事通信网络 攻击策略 鲁棒性 进化优化 

分 类 号:TP391[自动化与计算机技术—计算机应用技术] E919[自动化与计算机技术—计算机科学与技术]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象