Proceedings of the International Conference on Recent Advances in Materials, Processes and Technology for Sustainability (RAMPTS 2025)

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Study of the feasibility of using ANN for modelling Seismic Response of RC structures

Authors
C. A. Malavika1, *, Mini Koshy1
1Department of Civil Engineering, Rajiv Gandhi Institute of Technology, Kottayam, India
*Corresponding author. Email: 23mc2169@rit.ac.in
Corresponding Author
C. A. Malavika
Available Online 25 December 2025.
DOI
10.2991/978-94-6463-922-3_3How to use a DOI?
Keywords
Artificial Neural Networks (ANNs); Multilayer Perceptron (MLP); Root Mean Squared Error (RMSE); Coefficient of Determination (R2)
Abstract

This study explores the application of Artificial Neural Networks (ANNs) for predicting the seismic behavior of reinforced concrete (RC) buildings and bridges. The study aims to develop and validate ANN models to enhance the seismic assessment of structural integrity, focusing on both the structural response and energy demand under seismic and multi-hazard conditions. Two ANN models are developed using datasets obtained from existing literature. The ANN models are trained and validated using MATLAB software, employing a Multilayer Perceptron (MLP) architecture. The models are evaluated using performance metrics such as Root Mean Squared Error (RMSE) and the Coefficient of Determination (R2), which demonstrate high predictive accuracy. The results show that the ANN models can accurately predict structural responses and energy demands with minimal error, making them effective tools for seismic performance evaluation. Pearson correlation analysis further reveals the relationships between input parameters, providing valuable insights into factors influencing the seismic behavior of the structures. The study highlights the potential of AI-based models to streamline the seismic assessment process, reduce computational costs, and improve the accuracy of predictions for RC structures subjected to seismic and blast forces.

Copyright
© 2025 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 Recent Advances in Materials, Processes and Technology for Sustainability (RAMPTS 2025)
Series
Atlantis Highlights in Material Sciences and Technology
Publication Date
25 December 2025
ISBN
978-94-6463-922-3
ISSN
2590-3217
DOI
10.2991/978-94-6463-922-3_3How to use a DOI?
Copyright
© 2025 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  - C. A. Malavika
AU  - Mini Koshy
PY  - 2025
DA  - 2025/12/25
TI  - Study of the feasibility of using ANN for modelling Seismic Response of RC structures
BT  - Proceedings of the International Conference on Recent Advances in Materials, Processes and Technology for Sustainability (RAMPTS 2025)
PB  - Atlantis Press
SP  - 21
EP  - 26
SN  - 2590-3217
UR  - https://doi.org/10.2991/978-94-6463-922-3_3
DO  - 10.2991/978-94-6463-922-3_3
ID  - Malavika2025
ER  -