*Result*: 基于数字高程模型和人工蜂群算法的地面防空部署策略.
*Further Information*
*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 bee colony (ABC) algorithm was proposed. As for the strategy, the air defense efficiency is used as the evaluation index, and the DEM is 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 is iteratively found through the ABC algorithm. The ABC algorithm is used to improve the real-time deployment strategy of ground air defense equipment. 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. [ABSTRACT FROM AUTHOR]*
*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 (digital elevation model, DEM) 与人工蜂群 (artificial bee colony, ABC) 算法的部署 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。仿真结果表明, 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 FROM AUTHOR]*