1673-159X

CN 51-1686/N

基于数字高程模型和人工蜂群算法的地面防空部署策略

Ground Air Defense Deployment Strategy Based onDigital Elevation Model and Artificial Bee Colony Algorithm

  • 摘要: 针对地面防空装备部署优化问题中部署策略实时性不高、合理性差等问题,提出一种融合数字高程模型(DEM)与人工蜂群(ABC)算法的创新部署策略:以防空效能作为评估指标,在设定防空效能指标的前提下,把DEM作为先验信息对部署区域进行筛选,再通过ABC算法迭代寻找部署位置。该策略一方面利用ABC算法提高地面防空装备部署策略实时性,另一方面借助DEM数据,提高部署策略的合理性。仿真表明,与经典群智能优化算法相比,该策略能有效减少算法迭代次数,并且能取得更合理的部署方案。

     

    Abstract: In order to solve the problems of low real-time and poor rationality of the deployment strategy in the deployment optimization problem of ground air defense equipment, an innovative deployment strategy integrating digital elevation model (DEM) and artificial swarm (ABC) algorithm was proposed: the air defense efficiency was used as the evaluation index, and the DEM was used as the prior information to screen the deployment area under the premise of setting the air defense efficiency index, and then the deployment location was iteratively found through the ABC algorithm. On the one hand, the ABC algorithm is used to improve the real-time deployment strategy of ground air defense equipment, and on the other hand, the rationality of the deployment strategy is improved with the help of DEM data. Simulation results show that compared with the classical swarm intelligence optimization algorithm, the proposed strategy can effectively reduce the number of algorithm iterations and obtain a more reasonable deployment scheme.

     

/

返回文章
返回