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| 基于遗传算法的Al-5%Cu合金电脉冲孕育处理参数优化 | |
| 引用本文： | 王冰,王建中,张震斌,齐锦刚,苍大强. 基于遗传算法的Al-5%Cu合金电脉冲孕育处理参数优化[J]. 铸造技术, 2007, 28(8): 1043-1045 |
| 作者姓名： | 王冰 王建中 张震斌 齐锦刚 苍大强 |
| 作者单位： | 1. 北京科技大学冶金与生态工程学院,北京,100083;辽宁工学院材料与化学工程学院,辽宁,锦州,121001 2. 辽宁工学院材料与化学工程学院,辽宁,锦州,121001 3. 北京科技大学冶金与生态工程学院,北京,100083 |
| 摘 要： | 以实验为基础,利用神经网络和遗传算法优化Al-5%Cu合金的电脉冲孕育处理工艺参数。神经网络的输入参数为脉冲电压、脉冲时间和电脉冲孕育处理时熔体温度,输出参数是合金凝固组织的晶粒度。在神经网络训练的基础上,采用遗传算法优化神经网络的输入参数。结果表明,神经网络和遗传算法的组合建模获得了较好的优化结果。 |
| 关 键 词： | 电脉冲孕育处理 人工神经网络 BP算法 Al-Cu合金 |
| 文章编号： | 1000-8365（2007）08-1043-03 |
| 修稿时间： | 2006-12-072007-04-28 |
Optimization of Electric Pulse Modification Parameters in Al-5%Cu Alloy Using Neural Networks and Genetic Algorithms |
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| WANG Bing,WANG Jian-zhong,ZHANG Zhen-bin,QI Jin-gang,CANG Da-qiang. Optimization of Electric Pulse Modification Parameters in Al-5%Cu Alloy Using Neural Networks and Genetic Algorithms[J]. Foundry Technology, 2007, 28(8): 1043-1045 | |
| Authors: | WANG Bing WANG Jian-zhong ZHANG Zhen-bin QI Jin-gang CANG Da-qiang |
| Affiliation: | 1. School of Metallurgical and Ecological Engineering, University of Science and Technology, Beijing 100083, China; 2. Department of Material and Chemical Engineering, Liaoning Institute of Technology, Jinzhou 121001, China |
| Abstract: | Based on the experiments an optimal pattern of the electric pulse modification for Al-5%Cu was investigated using neural networks and genetic algorithms.The input parameters of the artificial neural network(ANN) are the voltage of electric pulse,electric pulse time and temperature of molten alloy.The outputs of the ANN model are the grain size of Al-5%Cu alloy.Based the successfully trained ANN model,genetic algorithms(GA) are used to optimize the input parameters of the model.The good optimization can be obtained through the integrated mode of neural networks and genetic algorithms. |
| Keywords: | Electric pulse modification Artificial neural network BP arithmetic mode AI-Cu alloy |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |