| 基于混沌退火算法和BPNN模型的末敏弹系统效能参数优化 |
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| 引用本文： | 张静,郝庆丽.基于混沌退火算法和BPNN模型的末敏弹系统效能参数优化[J].兵工自动化,2006,25(4):15-16. |
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| 作者姓名： | 张静 郝庆丽 |
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| 作者单位： | 襄樊学院,物理系,湖北,襄樊,441000;重庆铁马工业集团有限公司,工艺工程部,重庆,400050 |
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| 摘 要： | 基于混沌退火算法和BPNN模型的末敏弹系统效能参数优化,引入贝叶斯正则化方法的BPNN模型,使神经网络具有自适应性和推广能力.交替使用贝叶斯正则化和混沌退火算法,对网络参数进行优化,并对训练后的网络用系统效能参数.结果表明该模型不仅能拟合原系统,而且末敏弹系统效能参数更优,命中率更高.
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| 关 键 词： | 末敏弹 系统效能参数 贝叶斯正则化 混沌退火算法 |
| 文章编号： | 1006-1576（2006）04-0015-02 |
| 收稿时间： | 2006-01-17 |
| 修稿时间： | 2006-02-10 |
Optimal Research of System Efficiency Parameters About Terminal-Sensitive Projectiles Based on Algorithms of Chaos-Annealing Strategy and BPNN Model |
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| ZHANG Jing,HAO Qing-li.Optimal Research of System Efficiency Parameters About Terminal-Sensitive Projectiles Based on Algorithms of Chaos-Annealing Strategy and BPNN Model[J].Ordnance Industry Automation,2006,25(4):15-16. |
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| Authors: | ZHANG Jing HAO Qing-li |
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| Affiliation: | 1. Dept. of Physics, Xiangfan University, Xiangfan 441000, China; 2. Dept. Techniques Engineering, Chongqing Tiema Industries Cooperation, Chongqing 400050, China |
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| Abstract: | Efficiency parameters optimization about terminal-sensitive projectiles was based on algorithms of chaos-Annealing strategy and BPNN model. The BPNN model of Bayesian regularization method was adopted to create the adaptivity and generalization of BPNN. The Bayesian regularization method and algorithms of chaos-annealing strategy were used by turns to optimize the network parameters; and the system efficiency parameters were used in trained network. The results shows that the model could fit the original system, and the efficiency parameters of terminal-sensitive projectile system are better and hit rate is higher. |
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| Keywords: | Terminal-sensitive projectile Efficiency parameters optimization Bayesian regularization Algorithms of chaos-annealing strategy |
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