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基于自适应遗传算法的防空兵最优火力配置 被引量:2

Optimum Firepower Distribution for Caboodle of Air Defense Force Based on Adaptive Genetic Algorithm
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摘要 基于遗传算法的防空兵最优火力配置,运用战场目标价值和防空兵火力配置情况建立。最大限度发挥武器火力单位效能并达到最大毁伤效果。步骤包括:采用实数编码,通过构建染色体,生成初始群种;计算适应度,检验初始群种;操作遗传算子并改进选择、交叉、变异等操作。最后求解最优解,找出最优的配置方案。在该算法中,提出了1种既考虑进化代数对算法的影响,又考虑到每代不同个体适应度作用的自适应交叉概率和变异概率。 Optimum firepower distribution model for caboodle of air defense force based on genetic algorithm is established by using the battlefield object value and air defense firepower distribution. The model can exert the highest point of firepower unit efficiency of weapon and realize the most damage effect. The steps includes adopting real number to code, creating original community through building chromosome; calculating the degree of adaptation, checking out the original community; manipulating the inherit algorithm operators and ameliorating the manipulation of election, chiasma, variation and so on. At last, calculate the optimum selection and find out the optimum select of distributive project. The adaptive crossover probability and adaptive mutation probability are proposed, which consider the influence of every generation to algorithm and the effect of different individual fitness in every generation.
作者 潘伟
出处 《系统仿真技术》 2010年第2期88-91,共4页 System Simulation Technology
基金 国家自然科学基金资助项目(60474069)
关键词 自适应遗传算法 防空兵 最优火力 交叉概率 变异概率 adaptive genetic algorithm caboodle of air defense force optimum firepower crossover probability mutation probability
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