Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (2): 152-157.DOI: 10.3778/j.issn.1002-8331.1810-0192

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Projection Pursuit Threat Target Assessment Model Based on Chaotic Moth-Flame Optimization Algorithm

LI Hongwei, CHEN Liang, BAI Jingbo   

  1. 1.Field Engineering College, Army Engineering University of PLA, Nanjing 210007, China
    2.Automobile NCO Academy, Army Military Transportation University, Bengbu, Anhui 233011, China
  • Online:2020-01-15 Published:2020-01-14

基于CMFO算法的投影寻踪威胁目标评估模型

李宏伟,陈亮,白景波   

  1. 1.陆军工程大学 野战工程学院,南京 210007
    2.军事交通学院 汽车士官学校,安徽 蚌埠 233011

Abstract: In order to improve the accuracy of threat assessment and rank the threat targets quickly, a projection pursuit threat target assessment model based on Chaotic Moth-Flame Optimization(CMFO) algorithm is proposed. Firstly, a new swarm intelligence algorithm, Moth-Flame Optimization(MFO), is introduced, and chaotic maps is introduced to improve the performance of MFO. Secondly, the flow of the projection pursuit threat target assessment model is given, and the method steps of solving the optimal projection direction based on CMFO are given too. Finally, three examples of target threat assessment are selected to compare with other assessment methods. The comparison results show that the model is simple and effective, which provides a new method for rapid and accurate target threat assessment.

Key words: threat assessment, projection pursuit, chaotic maps, Moth-Flame Optimization(MFO)

摘要: 为了提高威胁目标评估的准确性,快速对威胁目标进行排序,提出了一种基于混沌飞蛾火焰优化(Chaotic Moth-Flame Optimization,CMFO)算法的投影寻踪威胁目标评估模型。简单介绍了一种新的群智能算法——飞蛾火焰优化算法(Moth-Flame Optimization,MFO),并引入混沌映射提高了MFO的性能。给出了投影寻踪威胁目标评估模型的算法流程,同时给出了基于CMFO求解最佳投影方向的方法步骤。选取了3个目标威胁评估的算例,进行实验分析,并与其他评估方法进行比较。比较结果表明该评估模型简单、有效,为快速、准确实现目标威胁评估提供了一种新的方法。

关键词: 威胁评估, 投影寻踪, 混沌映射, 飞蛾火焰算法