| 基于改进的微粒群算法的板形模式识别方法 |
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| 引用本文： | 郑德忠,闫涛,王志勇.基于改进的微粒群算法的板形模式识别方法[J].冶金自动化,2007,31(6):16-19,22. |
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| 作者姓名： | 郑德忠 闫涛 王志勇 |
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| 作者单位： | 1. 燕山大学,电气工程学院,河北,秦皇岛,066004
2. 燕山大学 |
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| 摘 要： | 针对在实际生产中板形信号识别精度不高的问题,通过对板形信号和板形识别数学模型的分析,采用基于混沌序列的微粒群寻优算法对板形信号进行识别。以勒让德正交多项式作为板形缺陷的基模式,将板形信号模式识别过程转化为函数的优化问题,有效地提高了算法的寻优效果,改进了板形信号模式识别的速度和精度。
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| 关 键 词： | 板形模式 微粒群寻优算法 混沌序列 |
| 文章编号： | 1000-7059（2007）06-0016-04 |
| 收稿时间： | 2007-07-20 |
| 修稿时间： | 2007-09-11 |
Shape pattern recognition method based on improved particle swarm optimization algorithm |
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| ZHENG De-zhong,YAN Tao,WANG Zhi-yong.Shape pattern recognition method based on improved particle swarm optimization algorithm[J].Metallurgical Industry Automation,2007,31(6):16-19,22. |
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| Authors: | ZHENG De-zhong YAN Tao WANG Zhi-yong |
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| Abstract: | For solving the problem that the traditional shape pattern recognition method was poor performance and low precision in practical application,by analyzing the shape signal and mathematical model of shape recognition,a new shape pattern recognition method based on improved Particle Swarm Optimization(PSO)algorithm is presented.Legendre polynomial as base model of shape defect pattern is used to transfer pattern recognition process into a function optimization problem.And,pattern recognition optimization results are further improved. |
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| Keywords: | shape pattern PSO algorithm chaos sequence |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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