基于Elman神经网络和Copula函数的多维装备效能评估模型

杨梓鑫;薛源;孙畅;徐浩军;韩欣珉

兵工学报 ›› 2020, Vol. 41 ›› Issue (8) : 1633-1645.

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  • 主管：中国科学技术协会

    主编：许毅达

    ISSN 1000-1093

    　

  • 主办：中国兵工学会

    出版：《兵工学报》 编辑部

    CN 11-2176/TJ

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兵工学报 ›› 2020, Vol. 41 ›› Issue (8) : 1633-1645. DOI: 10.3969/j.issn.1000-1093.2020.08.018
论文

基于Elman神经网络和Copula函数的多维装备效能评估模型

  • 杨梓鑫1， 薛源2,3， 孙畅1， 徐浩军3， 韩欣珉3
作者信息 +

Multidimensional Equipment Effectiveness Evaluation Model Based on Elman Neural Network and Copula Function

  • YANG Zixin1, XUE Yuan2,3, SUN Chang1, XU Haojun3, HAN Xinmin3
Author information +
文章历史 +

摘要

针对当前空战装备效能评估数据呈现出的非线性、多维性和耦合性等特征，将Elman神经网络与Copula函数相结合，提出了一种多维装备效能的评估模型。基于现代化空战特点建立效能评估指标体系的同时，结合战场环境与信息化空中对抗体系的仿真数据，利用Elman神经网络的权值参数自学习能力以及对非线性数据的良好拟合性，得到了边缘分布的预测模型及分布类型；针对分布数据之间的强耦合特征，选取Gumbel Copula函数、Clayton Copula函数、T-Copula函数、Frank Copula函 数、Joe Copula函数5种常用Archimedean Copula函数对变量间的相关性进行构造，通过对参数辨识和拟合优度结果进行对比，发现基于T-Copula函数所构建的联合分布模型与原始数据分布最为契合。以概率统计指标为评估依据，将该方法与传统方法进行了对比验证，得出了该方法的预测精度及适用范围均有所提升的结论。

Abstract

For the characteristics of non-linear, multidimensionality and coupling in the current air combat equipment effectiveness evaluation data, a multidimensional equipment effectiveness evaluation model is proposed by combining Elman neural network with Copula function. An effectiveness evaluation index system is established based on the characteristics of modern air combat, and the self-learning ability of the weight parameters of Elman neural network and the good fit to the non-linear data are used to obtain the prediction model and type of distribution based on the simulation data of the battlefield environment and the information-based air confrontation system. According to the strong coupling characteristics of the distribution data, five common Archimedean Copula functions, i.e., Gumbel Copula, Clayton Copula, T-Copula, Frank Copula, and Joe Copula, are selected to construct the correlation between variables. By comparing the results of parameter identification and goodness of fit, it is found that the joint distribution model constructed by T-Copula function is most suitable for the original data distribution. The proposed method was compared with the traditional method based on the probabilistic statistics index. The result shows that the proposed method has higher prediction accuracy and a wider scope of application.

关键词

装备效能 / 相关性 / 联合分布模型 / Elman神经网络 / Copula函数

Key words

equipmenteffectiveness / correlation / jointdistributionmodel / Elmanneuralnetwork / Copulafunction

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杨梓鑫， 薛源， 孙畅， 徐浩军， 韩欣珉. 基于Elman神经网络和Copula函数的多维装备效能评估模型. 兵工学报. 2020, 41(8): 1633-1645 https://doi.org/10.3969/j.issn.1000-1093.2020.08.018
YANG Zixin, XUE Yuan, SUN Chang, XU Haojun, HAN Xinmin. Multidimensional Equipment Effectiveness Evaluation Model Based on Elman Neural Network and Copula Function. Acta Armamentarii. 2020, 41(8): 1633-1645 https://doi.org/10.3969/j.issn.1000-1093.2020.08.018

基金

国家自然科学基金面上项目(61873351)； 国家自然科学基金项目（61503406）

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