Prediction of Shear Characteristics of Unsaturated Soil Based on BP Neural Network

Prediction of Shear Characteristics of Unsaturated Soil Based on BP Neural Network

The prediction model of shear strength parameters of unsaturated soil based on indoor test data is established by using BP neural network. Five kinds of network models with different number of hidden layer nodes are trained and studied, and the best network model is selected to conduct the predictio...

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Main Authors: Lei Liang Jia, Ri Jin Guang, Xie Shen Zhi
Format: Article
Language:English
Published: EDP Sciences 2020-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/25/e3sconf_caes2020_03034.pdf
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spelling doaj-2464db0c26834de897c39040e21c21892021-04-02T10:09:48ZengEDP SciencesE3S Web of Conferences2267-12422020-01-011650303410.1051/e3sconf/202016503034e3sconf_caes2020_03034Prediction of Shear Characteristics of Unsaturated Soil Based on BP Neural NetworkLei Liang Jia0Ri Jin Guang1Xie Shen Zhi2Department of Civil Engineering, Yanbian UniversityDepartment of Civil Engineering, Yanbian UniversityDepartment of Civil Engineering, Kyungpook National UniversityThe prediction model of shear strength parameters of unsaturated soil based on indoor test data is established by using BP neural network. Five kinds of network models with different number of hidden layer nodes are trained and studied, and the best network model is selected to conduct the prediction. The results show that the optimal BP network model is a single hidden layer structure of 8-16-2. Using this model to predict, the correlation coefficient and regression coefficient between the predicted value and the measured value are high, and the predicted result is reliable, so the method has certain practicability.https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/25/e3sconf_caes2020_03034.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Lei Liang Jia
Ri Jin Guang
Xie Shen Zhi
spellingShingle Lei Liang Jia
Ri Jin Guang
Xie Shen Zhi
Prediction of Shear Characteristics of Unsaturated Soil Based on BP Neural Network
E3S Web of Conferences
author_facet Lei Liang Jia
Ri Jin Guang
Xie Shen Zhi
author_sort Lei Liang Jia
title Prediction of Shear Characteristics of Unsaturated Soil Based on BP Neural Network
title_short Prediction of Shear Characteristics of Unsaturated Soil Based on BP Neural Network
title_full Prediction of Shear Characteristics of Unsaturated Soil Based on BP Neural Network
title_fullStr Prediction of Shear Characteristics of Unsaturated Soil Based on BP Neural Network
title_full_unstemmed Prediction of Shear Characteristics of Unsaturated Soil Based on BP Neural Network
title_sort prediction of shear characteristics of unsaturated soil based on bp neural network
publisher EDP Sciences
series E3S Web of Conferences
issn 2267-1242
publishDate 2020-01-01
description The prediction model of shear strength parameters of unsaturated soil based on indoor test data is established by using BP neural network. Five kinds of network models with different number of hidden layer nodes are trained and studied, and the best network model is selected to conduct the prediction. The results show that the optimal BP network model is a single hidden layer structure of 8-16-2. Using this model to predict, the correlation coefficient and regression coefficient between the predicted value and the measured value are high, and the predicted result is reliable, so the method has certain practicability.
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/25/e3sconf_caes2020_03034.pdf
work_keys_str_mv AT leiliangjia predictionofshearcharacteristicsofunsaturatedsoilbasedonbpneuralnetwork
AT rijinguang predictionofshearcharacteristicsofunsaturatedsoilbasedonbpneuralnetwork
AT xieshenzhi predictionofshearcharacteristicsofunsaturatedsoilbasedonbpneuralnetwork
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