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作 者:张菁 何友[1,3] 彭应宁 李刚[1] ZHANG Jing;HE You;PENG Yingning;LI Gang(Department of Electronic Engineering,Tsinghua University,Beijing 100086,China;Science and Technology on Complex Aviation Systems Simulation Laboratory,Beijing 100076,China;Research Institute of Information Fusion,Naval Aeronautical University,Yantai 264001,China)
机构地区:[1]清华大学电子工程系,北京100084 [2]复杂航空系统仿真重点实验室,北京100076 [3]海军航空大学信息融合研究所,山东烟台264001
出 处:《系统工程与电子技术》2018年第8期1754-1759,共6页Systems Engineering and Electronics
基 金:中国博士后科学基金(2018M631483)资助课题
摘 要:新一代战斗机技术特征论证是提升装备体系效能、指导技术发展方向、支撑新战斗机型号论证的重要工作。运用数据科学的思想,将传统的逆向归纳论证方法与机器学习类比,分析指出了其应用于新一代战斗机技术特征论证时将存在样本依赖度高、时效性差、不可解释、易过拟合等缺陷;然后提出一种基于数学规划的论证方法,以体系下的任务、环境和对抗能力为约束,以成本为优化目标,求解技术特征;最后以美海军和俄空军六代机为例验证了方法的可行性。The technology features demonstration of the next generation fighter is a significant issue for increasing military equipment performance, leading technology developments and supporting specific single weapon demonstration. This paper introduces data science to compare traditional backward induction methods with machine learning, and points out the weakness of traditional methods during the technical features demonstration of the next generation fighter, such as the sample dependent, delay, unexplainable and overfitting. Then a mathematical programming based demonstration method is proposed. This method obtains technology features of the next generation weapon with optimal overall cost, which is subject to capability requirements such as mission and environment requirements. Finally, the proposed method on US Navy and Russia Air Force sixthgeneration fighters is evaluated to prove its feasibility and superiority.
关 键 词:新一代战斗机 武器装备论证 数据科学 机器学习 数学规划 六代机
分 类 号:V37[航空宇航科学与技术—航空宇航推进理论与工程] E917[军事]
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