| 基于改进人工鱼群算法的WNN优化设计 |
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| 引用本文： | 唐雪琴,徐宗昌,甘旭升,黄书峰. 基于改进人工鱼群算法的WNN优化设计[J]. 现代防御技术, 2012, 40(1): 166-170 |
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| 作者姓名： | 唐雪琴 徐宗昌 甘旭升 黄书峰 |
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| 作者单位： | 1. 装甲兵工程学院,北京,100072
2. 空军工程大学工程学院,陕西西安,710038 |
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| 摘 要： | 针对人工鱼群算法优化设计小波神经网络(WNN)的缺陷,引入了视野范围与步长的自调整策略,以提高搜索效率和收敛速度。改进后的人工鱼群算法可在WNN的搜索空间中同时确定参数初始值和隐节点数。仿真实例验证了其有效性。
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| 关 键 词： | 小波神经网络 人工鱼群算法 优化设计 算法改进 |
WNN Optimization Design Based on Improved Artificial Fish Swarm Algorithm |
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| TANG Xue-qin , XU Zong-chang , GAN Xu-sheng , HUANG Shu-feng. WNN Optimization Design Based on Improved Artificial Fish Swarm Algorithm[J]. Modern Defence Technology, 2012, 40(1): 166-170 |
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| Authors: | TANG Xue-qin XU Zong-chang GAN Xu-sheng HUANG Shu-feng |
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| Affiliation: | 1(1.Academy of Armored Forces Engineering,Beijing 100072,China; 2.AFEU,Engineering Institute,Shannxi Xi’an 710038,China) |
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| Abstract: | In view of the shortcomings of AFSA(artificial fish swarm algorithm),the self-adjustment strategy on visual range and step size is introduced,so as to increase search efficiency and convergence rate.The improved AFSA may synchronously determine the parameters initiation value and hidden layer nodes number in search space.The simulation is given to illustrate the effectiveness of the method. |
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| Keywords: | wavelet neural network(WNN) artificial fish-swarm algorithm(AFSA) optimization design algorithm improvement |
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