Proceedings of the International Conference on Innovation & Entrepreneurship in Computing, Engineering & Science Education (InvENT 2024)

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Artificial Neural Network Modelling for Slope Stability Analysis of Slopes Stabilized with Piles Using Levenberg-Marquardt Algorithm

Authors
Noraida Mohd Saim1, *, Anuar Kasa2
1School of Civil Engineering, College of Engineering, Universiti Teknologi MARA, 40450, Shah Alam, Selangor, Malaysia
2Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia
*Corresponding author. Email: aidams2000@uitm.edu.my
Corresponding Author
Noraida Mohd Saim
Available Online 1 December 2024.
DOI
10.2991/978-94-6463-589-8_10How to use a DOI?
Keywords
ANN; Factor of Safety; Levenberg-Marquardt
Abstract

Slope stability is critical in geotechnical engineering, particularly in landslides regions. Conventional methods like Limit Equilibrium Methods (LEM) and Finite Element Methods (FEM) need enhancement through advanced computational technologies. This study explores the use of Artificial Neural Networks (ANN) to predict the stability of slopes reinforced with continuous bored piles. A total of 112 reinforced slope designs were evaluated using 2D FEM to determine the Factor of Safety (FOS), which served as the target for the ANN model. The ANN model was trained using Levenberg-Marquardt algorithm and evaluated for its accuracy using the coefficient of determination (R2) and Root Mean Square Error (RMSE). Results indicate that the ANN model demonstrates high accuracy in predicting FOS values, closely matching FEM calculations. The model offers a reliable and efficient tool for geotechnical engineers, providing faster and simpler alternatives for evaluating slope stability.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Innovation & Entrepreneurship in Computing, Engineering & Science Education (InvENT 2024)
Series
Advances in Computer Science Research
Publication Date
1 December 2024
ISBN
978-94-6463-589-8
ISSN
2352-538X
DOI
10.2991/978-94-6463-589-8_10How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Noraida Mohd Saim
AU  - Anuar Kasa
PY  - 2024
DA  - 2024/12/01
TI  - Artificial Neural Network Modelling for Slope Stability Analysis of Slopes Stabilized with Piles Using Levenberg-Marquardt Algorithm
BT  - Proceedings of the International Conference on Innovation & Entrepreneurship in Computing, Engineering & Science Education (InvENT 2024)
PB  - Atlantis Press
SP  - 87
EP  - 97
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-589-8_10
DO  - 10.2991/978-94-6463-589-8_10
ID  - Saim2024
ER  -