| 蚁群神经网络在涡流无损检测中的应用 |
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| 引用本文： | 谢颖,杨海涛,孙钦蕾.蚁群神经网络在涡流无损检测中的应用[J].科技资讯,2012(27):4-5. |
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| 作者姓名： | 谢颖 杨海涛 孙钦蕾 |
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| 作者单位： | 1. 装备指挥技术学院研究生院研究生五队,北京,101416
2. 军械工程学院,河北石家庄,050003 |
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| 摘 要： | 本文针对RBF神经网络参数选取问题,提出蚁群智能算法优化RBF神经网络,该算法利用正反馈机制迅速确定较优中心节点,同时利用其分布式计算特点避免算法过早的收敛。在涡流无损检测中的应用表明:蚁群算法提高了中心节点的聚类质量,优化了RBF网络结构,提高了识别的精度,应用效果良好。
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| 关 键 词： | RBF神经网络 蚁群算法 涡流无损检测 |
Application of Ant Colony Neural Network in Eddy Current Nondestructive Detecting |
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| Xie Ying,Yang Haitao,Sun Qinlei.Application of Ant Colony Neural Network in Eddy Current Nondestructive Detecting[J].Science & Technology Information,2012(27):4-5. |
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| Authors: | Xie Ying Yang Haitao Sun Qinlei |
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| Institution: | 2 ( 1. The Academy of Equipment Command and Technology, Beijing, 101416 2. Ordnance Engineering College,Shijiazhuang,050003) |
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| Abstract: | Ant colony algorithm is adopted to select the center of RBF network,It combines the distributed computing, positive feedback mechanism and greed search algorithm. In the search process, it is easy to obtain the global optimization and it has the shorter search time. In eddy current nondestructive detecting,the simulation shows that the construction of RBF network is optimized and the convergence and precision are improved. |
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| Keywords: | RBF network Ant Colony Algorithm Eddy current Nondestructive Detecting |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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