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论文:2019,Vol:37,Issue(2):424-432 |
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引用本文： |
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陈侠, 刘子龙, 梁红利. 基于GA-SLFRWNN的空中目标威胁评估[J]. 西北工业大学学报 |
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CHEN Xia, LIU Zilong, LIANG Hongli. Assessment of Aerial Target Threat Based on Genetic Algorithm Optimizing Fuzzy Recurrent Wavelet Neural Network[J]. Northwestern polytechnical university |
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| 基于GA-SLFRWNN的空中目标威胁评估 |
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| 陈侠, 刘子龙, 梁红利 |
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| 沈阳航空航天大学 自动化学院, 辽宁 沈阳 100136 |
| 摘要: |
| 针对空战中目标威胁评估系统非线性、评估难度大且富含不确定信息的问题，研究了基于遗传算法优化模糊递归小波神经网络（single-hidden-layer fuzzy recurrent wavelet neural network optimized by genetic algorithm，GA-SLFRWNN）的目标威胁评估方法。首先通过分析威胁评估的影响因素及其信息的模糊性，将RWNN嵌入FNN的后件部分，以实现增强自学习能力的目的，然后采用GA对模型初始参数进行优化选取，并提出了基于李雅普诺夫理论的最优学习率。仿真实验表明：相比于FNN和FRWNN，该算法提高了系统的稳定性，加快了收敛速度，增强了预测精度。 |
| 关键词:
目标威胁评估
模糊神经网络
模糊递归小波神经网络
遗传算法
最优学习率
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| Assessment of Aerial Target Threat Based on Genetic Algorithm Optimizing Fuzzy Recurrent Wavelet Neural Network |
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| CHEN Xia, LIU Zilong, LIANG Hongli |
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| School of Automatic, Shenyang University of Aerospace, Shenyang 100136, China |
| Abstract: |
| In target threat assessment of air combat, the evaluation system model is usually nonlinear and the assessment which is difficult to obtain also has some uncertain information. In order to effectively solve these problems, the Single-hidden-layer Fuzzy Recurrent Wavelet Neural Network Optimized by Genetic Algorithm (GA-SLFRWNN) is presented in this paper. In this new method, the influence factors for assessment and the ambiguity of their information are first analyzed. The RWNN are embed in the back part of FNN (fuzzy neural network) for the purpose of enhancing self-learning ability. Then GA is used to optimize the initial parameters of the model and the optimal learning rate based on Lyapunov theory is proposed. The simulation results show that the proposed algorithm improves the stability of the evaluation system, accelerates the convergence speed and enhances the prediction accuracy compared with the FNN and SLFRWNN. |
| Key words:
target threat assessment
fuzzy neural network
fuzzy recurrent wavelet neural network
genetic algorithm
optimal learning rate
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| 收稿日期: 2018-05-13
修回日期:
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| DOI: 10.1051/jnwpu/20193720424 |
| 基金项目: 国家自然科学基金（61503255）、航空科学基金（2016ZC54011）和辽宁省自然科学基金（2015020063）资助 |
| 通讯作者:
Email： |
| 作者简介: 陈侠(1962-),沈阳航空航天大学教授,主要从事无人机航迹规划研究。
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| 作者相关文章 |
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| 陈侠 在本刊中的所有文章 |
| 刘子龙 在本刊中的所有文章 |
| 梁红利 在本刊中的所有文章 |
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