Backpropagation Neural Network-Based Machine Learning Model for Prediction of Soil Friction Angle
Joint Authors
Nguyen, Thuy-Anh
Ly, Hai-Bang
Pham, Binh Thai
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-24
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
In the design process of foundations, pavements, retaining walls, and other geotechnical matters, estimation of soil strength-related parameters is crucial.
In particular, the friction angle is a critical shear strength factor in assessing the stability and deformation of geotechnical structures.
Practically, laboratory or field tests have been conducted to determine the friction angle of soil.
However, these jobs are often time-consuming and quite expensive.
Therefore, the prediction of geo-mechanical properties of soils using machine learning techniques has been widely applied in recent times.
In this study, the Bayesian regularization backpropagation algorithm is built to predict the internal friction angle of the soil based on 145 data collected from experiments.
The performance of the model is evaluated by three specific statistical criteria, such as the Pearson correlation coefficient (R), root mean square error (RMSE), and mean absolute error (MAE).
The results show that the proposed algorithm performed well for the prediction of the friction angle of soil (R = 0.8885, RMSE = 0.0442, and MAE = 0.0328).
Therefore, it can be concluded that the backpropagation neural network-based machine learning model is a reasonably accurate and useful prediction tool for engineers in the predesign phase.
American Psychological Association (APA)
Nguyen, Thuy-Anh& Ly, Hai-Bang& Pham, Binh Thai. 2020. Backpropagation Neural Network-Based Machine Learning Model for Prediction of Soil Friction Angle. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1201691
Modern Language Association (MLA)
Nguyen, Thuy-Anh…[et al.]. Backpropagation Neural Network-Based Machine Learning Model for Prediction of Soil Friction Angle. Mathematical Problems in Engineering No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1201691
American Medical Association (AMA)
Nguyen, Thuy-Anh& Ly, Hai-Bang& Pham, Binh Thai. Backpropagation Neural Network-Based Machine Learning Model for Prediction of Soil Friction Angle. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1201691
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1201691