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机构地区:[1]北方自动控制技术研究所,山西 太原
出 处:《运筹与模糊学》2024年第1期1130-1137,共8页Operations Research and Fuzziology
摘 要:机场跑道作为均匀分布面目标,在对打击机场跑道的弹着点进行分配时,通常采用均匀分配法或蒙特卡罗法进行分配。本文通过概率法,充分考虑子弹射击误差和目标观测误差,建立弹着点与有效封控面积之间函数关系模型,运用遗传算法进行全局择优,快速准确地计算出最大有效封控面积下的近似最优弹着点位置。即解决均匀分配的可靠性问题,又相比于蒙特卡洛算法在计算效率上大大提升,并给出不同尺寸跑道计算出近似最优弹着点所需的迭代次数,为工程应用进一步提高计算效率提供数据需求。Airport runways, as targets with uniform distribution surface, are usually distributed by uni-form distribution method or Monte Carlo method when the impact points against airport runways are distributed. In this paper, the probability method is used to fully consider the bullet firing error and target observation error, establish the functional relational model between the impact point and the effective containment area, and use genetic algorithm to conduct global optimization, quickly and accurately calculate the approximate optimal impact point position under the maximum effective containment area. It not only solves the reliability problem of uniform distribution, but also greatly improves the calculation efficiency compared with the Monte Carlo algorithm. It also gives the number of iterations required to calculate the approximate optimal impact point for runways of different sizes, providing data requirements for engineering appli-cations to further improve the calculation efficiency.
分 类 号:TP3[自动化与计算机技术—计算机科学与技术]
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