期刊文献+

基于量子遗传算法的港口目标瞄准点选择 被引量:2

Choice for aim point of port target based on quantum genetic algorithm
下载PDF
导出
摘要 使用多枚巡航导弹攻击港口目标时,瞄准点选择非常关键,传统方法所用模型较为简单、算法较为耗时。为此,根据港口子目标幅员特性,构建矩形化子目标,并按离差最大思想赋予威胁指数。从毁伤效果出发,以毁伤下界为限,构建港口目标威胁消除模型。将量子理论引入遗传算法,构建量子遗传融合算法,并用其求解瞄准点分布。仿真结果表明,得出的瞄准点具有较高可靠性,验证了模型的有效性,所用算法能在短时间内找出最优解,提高了解的收敛速度。 When port targets are hit by multi-cruise missiles,aim points are very important,but traditional models are much simple and algorithms take much time.Rectangular sub-targets are constructed according to their characters,and intimidator indexes are given by maximal deviations.From the hit effect,the port targets deterrence elimination model based on the damage bottom is built.Quantum genetic algorithm is gotten by combining the quantum theory and genetic algorithm,which is used to above model.Results show that distribution of aim points is believable,which indicates the model is effective,and the algorithm can find the best results quickly,which indicates the speed for outcomes is advanced.
出处 《系统工程与电子技术》 EI CSCD 北大核心 2012年第4期732-736,共5页 Systems Engineering and Electronics
关键词 巡航导弹 港口目标 瞄准点 量子遗传算法 优化 cruise missile port target aim point quantum genetic algorithm(QGA) optimization
分类号 E9 [军事]
  • 相关文献

参考文献15

  • 1Bardnis F. Kill vehicle effectiveness for boost phase interception of ballistic missiles[D].California:Naval Postgraduate School,2004.
  • 2王威,张多林.巡航导弹典型目标瞄准点优化方法研究[J].弹箭与制导学报,2008,28(3):98-100. 被引量:1
  • 3Henninger A E. Individual combatant's weapons firing algorithm[ADA520736][R].Institute for Defense Analysis,2010.
  • 4Patch J. Obstacles to effective joint targeting[R].ADA480949,Institute for Defense Analysis,2007.
  • 5雷宁利,张永强.混合相依目标群瞄准点优选方法研究[J].系统工程与电子技术,2004,26(9):1234-1235. 被引量:7
  • 6Gulfem I,Gulcin B. Using a multi-criteria decision making approach to evaluate mobile phone alternatives[J].Computer Standards and Interfaces,2007,(02):265-274.
  • 7Wang J,Wang M H. The research of selecting aim-points for penetration cluster warhead attacking runway based on genetic algorithms and Monte Carlo[A].2010.343-347.
  • 8Jin X Y,Davis C H. Vector-guided vehicle detection from high-resolution satellite imagery[A].2004.920-924.
  • 9舒健生,武健,王少峰,刘博.基于粒子群算法打击指挥系统瞄准点优化[J].西南科技大学学报,2009,24(4):70-74. 被引量:1
  • 10Salam A,Defersha F M,Bhuiyan N. A case study on target cost estimation using a genetic algorithm and a backpropagation based neural network[A].2010.1-9.

二级参考文献35

  • 1王芳,冯顺山,俞为民.“超压—冲量”毁伤准则及其等毁伤曲线研究[J].弹箭与制导学报,2003,23(S2):126-130. 被引量:22
  • 2雷宁利,张永强.混合相依目标群瞄准点优选方法研究[J].系统工程与电子技术,2004,26(9):1234-1235. 被引量:7
  • 3WHITTEN G.Automated missile aim point selection technology,AD-A300813[R].1995.
  • 4FLORIOS B.Kill vehicle effectiveness for boost phase interception of ballistic missiles[D].Monterey,California:Master of Science in Electrical Engineering,Naval Postgraduate School,2004.
  • 5HSU D Y.Probability of hitting a specified target region with the three-dimensional correlated random variables and aim point offset from the target[J].IEEE Position Location and Navigation Symposium,2002,(4):113-119.
  • 6傅常海,黄柯棣,赵玉立,等.爆炸冲击波对建筑物毁伤机理与毁伤效应数值模拟分析[A].见:罗绍凯,龚自正主编.数学、力学、物理学、高新技术研究进展-2008(12)卷[C].北京:科学出版社,2008.
  • 7JGJ125-99.危险房屋鉴定标准[S],2000.
  • 8Nones, L. Cooperative Teaming Using Advice Exchange [ M ]. Berlin, Heldellberg, Germany : Springer-Verlag,2003.33 - 48.
  • 9Cheng S T,Tao M H.Quantum cooperative search algorithm for 3-SAT[J].Journal of Computer and System Sciences,2007,73:123-136.
  • 10Narayanan A,Moore M.Quantum inspired genetic algorithms[C]//Proceedings of the 1996 IEEE International Conference on Evolutionary Computation (ICEC96),Nogaya,Japan,1996:61-66.

共引文献23

同被引文献12

引证文献2

二级引证文献14

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部