系统仿真学报 ›› 2015, Vol. 27 ›› Issue (1): 43-49.

• 建模与仿真理论及方法 • 上一篇    下一篇

基于Elman神经网络的作战效能预测模型研究

李小喜1, 陈浩光2, 李大喜3, 陈疆萍4   

  1. 1.装备学院研究生管理大队,北京 101416;
    2.装备学院装备采办系,北京 101416;
    3.空军工程大学防空反导学院,西安 710038;
    4.中国人民解放军93942部队,咸阳 712000
  • 收稿日期:2013-12-20 修回日期:2014-03-23 发布日期:2020-09-02
  • 作者简介:李小喜(1983-),男,甘肃平凉,博士生, 研究方向为武器装备发展论证与卫星体系优化;陈浩光 (1967-),男,江西瑞金,教授,研究方向为武器装备发 展论证与效能评估;李大喜(1983-),男,甘肃平凉,博 士生,研究方向为武器装备发展论证与体系规划。

Study on Combat Effectiveness Prediction Model Using Elman Feedback Network

Li Xiaoxi1, Chen Haoguang2, Li Daxi3, Chen Jiangping4   

  1. 1. Department of Graduate Management, Equipment Academy, Beijing 101416, China;
    2. Department of Equipment Acquisition, Equipment Academy, Beijing 101416, China;
    3. Air and Missile Defense Institute, Air Force Engineering University, Xi’an 710038, China;
    4. Unit 93942 of PLA, Xianyang 712000, China
  • Received:2013-12-20 Revised:2014-03-23 Published:2020-09-02

摘要: 针对军事系统作战效能预测问题,采用基于支持向量回归的指标权重挖掘方法,通过比较偏导确定影响作战效能的关键因素,将优化后的效能指标和效能值分别作为模型的输入和输出,建立基于Elman神经网络的效能预测模型。并将其应用于C4ISR系统的动态作战效能预测分析中。结果表明,该方法能够减少不确定因素的影响,在一定程度上降低了预测模型的复杂度,为科学预测军事系统作战效能提供了有效的技术支撑。

关键词: 作战效能, Elman神经网络, 支持向量机, 效能预测模型

Abstract: To deal with combat effectiveness prediction of the military system, a SVR-based crucial evaluation indexes mining method was carefully investigated. The key indexes in the effectiveness evaluation were found by comparing partial derivatives. The model of efficiency prediction based on Elman neural networks, which used effective optimized indexs and values as input and output, was exerted to combat effectiveness prediction of C4ISR. The results show that the method can reduce the complexity of prediction model, and avoid uncertain factors existing in system, which provide effective technical support for the combat effectiveness prediction scientifically.

Key words: combat effectiveness, Elman neural networks, SVM, effectiveness prediction model

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