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| 用粗集-模糊神经网络评定空袭目标威胁程度 | |
| 引用本文： | 罗艳春,郭立红,康长青,李念峰.用粗集-模糊神经网络评定空袭目标威胁程度[J].光电工程,2008,35(3):10-15. |
| 作者姓名： | 罗艳春 郭立红 康长青 李念峰 |
| 作者单位： | 1. 中国科学院长春光学精密机械与物理研究所,长春,130033;中国科学院研究生院,北京,100039;空军航空大学,长春,130022 2. 中国科学院长春光学精密机械与物理研究所,长春,130033 3. 中国科学院长春光学精密机械与物理研究所,长春,130033;中国科学院研究生院,北京,100039 |
| 基金项目： | 中国科学院知识创新工程项目 |
| 摘 要： | 针对模糊神经网络运算过程中,当模糊规则较多时,网络学习速度慢,方法实时性差的缺点,本文提出采用粗糙集理论对该模型进行优化,该方法利用粗集数据分析方法,通过知识约简从数据中推理逻辑规则,并用约简后规则集作为模糊神经网络的规则将输入映射到输出的子空间上:在这个子空间上用改进的BP算法训练进行逼近.实验结果表明:通过粗集数据挖掘后提取的规则,不仅规则数目减少,且规则是不完全规则,减少了网络输入维数和各层神经元的个数,提高了网络运算速度,满足了系统实时性要求. |
| 关 键 词： | 粗糙集 模糊神经网络 约简 威胁估计 粗集 模糊 神经网络 空袭目标 威胁程度 Fuzzy Neural Networks Rough Sets Applying Target Aerial Degree Threat 系统实时性 运算速度 神经元 网络输入维数 完全 规则数目 提取 数据挖掘 |
| 文章编号： | 1003-501X(2008)03-0010-06 |
| 收稿时间： | 2007/6/2 |
| 修稿时间： | 2007年6月2日 |
Assessing Threat Degree of Aerial Target by Applying Rough Sets and Fuzzy Neural Networks |
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| LUO Yan-chun,GUO Li-hong,KANG Chang-qing,LI Nian-feng.Assessing Threat Degree of Aerial Target by Applying Rough Sets and Fuzzy Neural Networks[J].Opto-Electronic Engineering,2008,35(3):10-15. | |
| Authors: | LUO Yan-chun GUO Li-hong KANG Chang-qing LI Nian-feng |
| Affiliation: | LUO Yan-chun1,2,3,GUO Li-hong1,KANG Chang-qing1,LI Nian-feng1,2 ( 1.Changchun Institute of Optics,Fine Mechanics , Physics,Chinese Academy of Sciences,Changchun 130033,China,2. Graduate School of Chinese Academy of Sciences,Beijing 100039,3. Aviation University of Air Force,Changchun 130022,China ) |
| Abstract: | When there are many fuzzy rules during Fuzzy-neural Networks (FNN) operation,the networks usually have slow learning speed and long running time. To solve this problem,a rough set theory was introduced to improve FNN model.Rough set data analysis method was used to obtain the reductive rules which were used as the fuzzy rules of the FNN.The input to the model was mapped into the output subspace by using these rules and the output of the system was approximated by improved BP algorithm training in this subsp... |
| Keywords: | rough sets fuzzy neural networks reduce threat assessment |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |
