BP神经网络在固结系数预测中的应用

Hong-Hu Zhu, Jianhui Fu, Fei Dai
{"title":"BP神经网络在固结系数预测中的应用","authors":"Hong-Hu Zhu, Jianhui Fu, Fei Dai","doi":"10.1109/ACTEA.2009.5227942","DOIUrl":null,"url":null,"abstract":"The application of artificial neural network (ANN) in the discipline of geotechnical engineering is discussed in this paper. A multi-layer error back-propagation (BP) feed-forward neural network model was proposed to predict an important geotechnical parameter, namely the consolidation coefficient. The conventional methods for predicting consolidation coefficient is briefly introduced. Based on the results of laboratory consolidation tests, the BP model was trained and used to determine the consolidation coefficient. The predicted values were compared to those determined by graphical methods. It is proved that the BP neural network approach yielded similar results compared with other methods.","PeriodicalId":308909,"journal":{"name":"2009 International Conference on Advances in Computational Tools for Engineering Applications","volume":"218 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of BP neural network in the prediction of consolidation coefficient\",\"authors\":\"Hong-Hu Zhu, Jianhui Fu, Fei Dai\",\"doi\":\"10.1109/ACTEA.2009.5227942\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The application of artificial neural network (ANN) in the discipline of geotechnical engineering is discussed in this paper. A multi-layer error back-propagation (BP) feed-forward neural network model was proposed to predict an important geotechnical parameter, namely the consolidation coefficient. The conventional methods for predicting consolidation coefficient is briefly introduced. Based on the results of laboratory consolidation tests, the BP model was trained and used to determine the consolidation coefficient. The predicted values were compared to those determined by graphical methods. It is proved that the BP neural network approach yielded similar results compared with other methods.\",\"PeriodicalId\":308909,\"journal\":{\"name\":\"2009 International Conference on Advances in Computational Tools for Engineering Applications\",\"volume\":\"218 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Advances in Computational Tools for Engineering Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACTEA.2009.5227942\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Advances in Computational Tools for Engineering Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACTEA.2009.5227942","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

本文讨论了人工神经网络在岩土工程学科中的应用。提出了一种多层误差反向传播(BP)前馈神经网络模型,用于预测重要岩土参数固结系数。简要介绍了预测固结系数的常用方法。在室内固结试验的基础上,对BP模型进行了训练,并用于确定固结系数。将预测值与图解法测定值进行比较。实验证明,BP神经网络方法与其他方法的结果相似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of BP neural network in the prediction of consolidation coefficient
The application of artificial neural network (ANN) in the discipline of geotechnical engineering is discussed in this paper. A multi-layer error back-propagation (BP) feed-forward neural network model was proposed to predict an important geotechnical parameter, namely the consolidation coefficient. The conventional methods for predicting consolidation coefficient is briefly introduced. Based on the results of laboratory consolidation tests, the BP model was trained and used to determine the consolidation coefficient. The predicted values were compared to those determined by graphical methods. It is proved that the BP neural network approach yielded similar results compared with other methods.
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:604180095
Book学术官方微信