基于人工神经网络的铝青铜超塑性预测及应用

Guo Junqing, Chen Fuxiao, Yang Yongshun, Li Hejun
{"title":"基于人工神经网络的铝青铜超塑性预测及应用","authors":"Guo Junqing, Chen Fuxiao, Yang Yongshun, Li Hejun","doi":"10.1109/ICNC.2010.5583350","DOIUrl":null,"url":null,"abstract":"The superplastic performances prediction of albronze based on artificial neural network was studied in this paper. Used Levenberg-Marquardt algorithm, the predication model of BP neural network which reflects the relationship between the superplastic performances and tension conditions was founded. The superplasticity and optimized condition of albronze were forecasted and the superplastic extrusion tests of solid cage was produced also. The results showed that the error of tests data and prediction was less than 8.5%. It was indicated that the prediction of albronze superplasticity used artificial neural network was effective and feasible.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"24 1","pages":"668-670"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Superplasticity prediction and application of albronze based on artificial neural network\",\"authors\":\"Guo Junqing, Chen Fuxiao, Yang Yongshun, Li Hejun\",\"doi\":\"10.1109/ICNC.2010.5583350\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The superplastic performances prediction of albronze based on artificial neural network was studied in this paper. Used Levenberg-Marquardt algorithm, the predication model of BP neural network which reflects the relationship between the superplastic performances and tension conditions was founded. The superplasticity and optimized condition of albronze were forecasted and the superplastic extrusion tests of solid cage was produced also. The results showed that the error of tests data and prediction was less than 8.5%. It was indicated that the prediction of albronze superplasticity used artificial neural network was effective and feasible.\",\"PeriodicalId\":87274,\"journal\":{\"name\":\"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications\",\"volume\":\"24 1\",\"pages\":\"668-670\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNC.2010.5583350\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2010.5583350","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文研究了基于人工神经网络的铝青铜超塑性性能预测。采用Levenberg-Marquardt算法,建立了反映超塑性性能与拉伸条件关系的BP神经网络预测模型。对铝青铜的超塑性和优化条件进行了预测,并进行了固体笼的超塑性挤压试验。结果表明,试验数据与预测误差均小于8.5%。结果表明,人工神经网络预测铝青铜超塑性是有效可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Superplasticity prediction and application of albronze based on artificial neural network
The superplastic performances prediction of albronze based on artificial neural network was studied in this paper. Used Levenberg-Marquardt algorithm, the predication model of BP neural network which reflects the relationship between the superplastic performances and tension conditions was founded. The superplasticity and optimized condition of albronze were forecasted and the superplastic extrusion tests of solid cage was produced also. The results showed that the error of tests data and prediction was less than 8.5%. It was indicated that the prediction of albronze superplasticity used artificial neural network was effective and feasible.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信