伞兵, 侯岳, 浦金云, 等. 舰艇损管指挥信息系统复杂网络结构建模及优化分析[J]. 中国舰船研究, 2022, 17(4): 220–227. doi: 10.19693/j.issn.1673-3185.02441
引用本文: 伞兵, 侯岳, 浦金云, 等. 舰艇损管指挥信息系统复杂网络结构建模及优化分析[J]. 中国舰船研究, 2022, 17(4): 220–227. doi: 10.19693/j.issn.1673-3185.02441
SAN B, HOU Y, PU J Y, et al. Analysis of structure modeling and optimization of complex network of warship damage control command information system[J]. Chinese Journal of Ship Research, 2022, 17(4): 220–227. doi: 10.19693/j.issn.1673-3185.02441
Citation: SAN B, HOU Y, PU J Y, et al. Analysis of structure modeling and optimization of complex network of warship damage control command information system[J]. Chinese Journal of Ship Research, 2022, 17(4): 220–227. doi: 10.19693/j.issn.1673-3185.02441

舰艇损管指挥信息系统复杂网络结构建模及优化分析

Analysis of structure modeling and optimization of complex network of warship damage control command information system

  • 摘要:
      目的  现代舰艇灾害突发性以及蔓延快速性的显著提升,对舰艇损管指挥网络的信息化水平提出了更高要求。基于损管指挥信息系统复杂的网络特性分析,构建该系统的网络拓扑模型。
      方法  针对当前模型存在的不足,在随机网络化方法的基础上,综合考虑损管指挥信息网络的节点属性和增加网络密度的成本因素,提出一种择优随机网络化的结构优化方法,并通过案例仿真对具体的优化流程予以演示。
      结果  仿真结果表明:指挥子网和设备子网的结构优化对整体网络性能的影响各异;相比传统的随机网络化方法,择优随机网络化方法的优化效能更高。
      结论  后续研究可从改变子网之间的连接方式入手,解决末级指挥节点度过高的问题,以进一步改善损管指挥信息网络的综合性能。

     

    Abstract:
      Objectives  The suddenness and rapidity of modern warship disasters have significantly intensified, and higher requirements have been put forward for the information level of the damage control (DC) command network. Based on the complex network characteristic analysis of a DC command information system, its network topology model is constructed.
      Methods  Aiming at the shortcomings of the current model, based on the stochastic networking method and considering the node attributes of the DC command information network and the cost of increasing network density, a structural optimization method for optimal stochastic networking is proposed, and the specific optimization process is demonstrated by case simulation.
      Results  The results show that the command and facilities subnets have different influences on network performance, and the improved random networking method performs better than the traditional random method in network structure optimization.
      Conclusions  Subsequent research can start by changing the connection mode between subnets to solve the problem of the terminal node of the command subnet being too high, thereby further improving the comprehensive performance of the DC command information network.

     

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