| 基于BP神经网络和遗传算法的刚挠背板设计 |
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| 引用本文： | 史经辉,吴兆华,黄春跃. 基于BP神经网络和遗传算法的刚挠背板设计[J]. 电子元件与材料, 2009, 28(6). DOI: 10.3969/j.issn.1001-2028.2009.06.019 |
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| 作者姓名： | 史经辉 吴兆华 黄春跃 |
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| 作者单位： | 桂林电子科技大学,机电工程学院,广西,桂林,541004 |
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| 基金项目： | 预研项目:广西研究生科研创新资助项目 |
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| 摘 要： | 选取加强筋宽度等5个关键因素,采用正交设计法采集刚挠背板基频形成训练样本。由试验确定BP神经网络拓扑结构。选用LM算法训练的BP神经网络(BPNN)作为遗传算法目标函数求解器,用于优化抗振结构。结果表明,网络拓扑结构为4-6-1时网络泛化能力强,测试误差小于1.6%;获得最优结构参数组合x1～x5分别为0.0039,0.004,0.0268,0.0242和0.0018m;优化后,基频提高92.7%,振幅降低82.77%,计算误差为0.636%。
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| 关 键 词： | 刚挠背板 BP神经网络 遗传算法 抗震设计 |
Anti-vibration design of rigid-flex backplane based on BP neural network and genetic algorithm |
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| SHI Jinghui,WU Zhaohua,HUANG Chunyue. Anti-vibration design of rigid-flex backplane based on BP neural network and genetic algorithm[J]. Electronic Components & Materials, 2009, 28(6). DOI: 10.3969/j.issn.1001-2028.2009.06.019 |
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| Authors: | SHI Jinghui WU Zhaohua HUANG Chunyue |
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| Affiliation: | School of Mechanical & Electrical Engineering;Guilin University of Electronic Technology;Guilin 541004;Guangxi Zhuangzu Zizhiqu;China |
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| Abstract: | In this study,stiffening width and other four parameters were selected as key factors.Training samples were generated based on the fundamental frequency of rigid-flex backplane collected using orthogonal design method.The topological structure of neural network was determined via testing.To optimize the anti-vibration structure,the back propagation neural networks(BPNN),trained by Levenberg-Marquardt(LM) algorithm,was used as the objective function solver for genetic algorithm(GA).The results indicate that,... |
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| Keywords: | rigid-flex backplane BP neural network genetic algorithm anti-vibration design |
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