基于图模型的海上自适应杀伤网生成与应用

Generation and application of maritime adaptive kill web based on graph model

  • 摘要:
    目的 旨在解决海上作战装备协同调度难题,提升作战效能。
    方法 本文提出一种基于图模型的海上自适应杀伤网生成方法。该方法涵盖4个关键部分:通过战场态势建模,实时接入并融合多源信息构建动态战场模型;利用复杂任务分解模块,将作战任务细化为可执行子任务并优化资源分配;基于装备关系和能力指标生成杀伤网,并在多重目标约束下优选;当装备资源变化时,通过冗余节点补充等方式自适应重构杀伤网。
    结果 经海上反导场景试验验证,该方法可有效解决战场态势信息处理、任务分解与建模、装备协同优化及动态调整等问题,能快速生成并优化杀伤网,实现多链条、多角度防御。
    结论 基于图模型的海上自适应杀伤网生成方法可提升现代海上作战整体效能和应对能力,未来将继续优化算法性能与系统响应能力,为军事作战提供更有力支持。

     

    Abstract:
    Objective To address the challenges of the coordinated scheduling of naval combat equipment and enhance combat effectiveness, this paper conducts research on the generation method of a maritime adaptive kill web based on a graph model.
    Method The proposed method encompasses four key parts. Through battlefield situation modeling, the real-time access and integration of multi-source information are carried out to construct a dynamic battlefield model. A complex task decomposition module is utilized to break down combat tasks into executable subtasks and optimize resource allocation. The kill web is generated based on equipment relationships and capability indicators, and optimized under multiple objective constraints. When the equipment resources change, the kill web is adaptively reconstructed through redundant node supplementation and other means.
    Results Verified by a maritime anti-missile scenario experiment, this method effectively solves the problems of battlefield situation information processing, task decomposition and modeling, and equipment collaborative optimization and dynamic adjustment, and can quickly generate and optimize a kill web to achieve multi-chain and multi-angle defense.
    Conclusions The proposed graph model-based maritime adaptive kill web generation method can improve the overall effectiveness and response ability of modern naval warfare. Future research will continue to optimize the algorithm performance and system response ability to provide stronger support for military operations.

     

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