Seismic performance prediction of reinforced concrete buildings using the RYTEIE method: a comparison of machine learning models

Rabia Nur Sağlam; Muhammed Veysi Güler; Mahmut Kaya; Mustafa Ulaş; Kürşat Esat Alyamaç

doi:10.29132/ijpas.1928087

Seismic performance prediction of reinforced concrete buildings using the RYTEIE method: a comparison of machine learning models

Abstract

This study aims to predict seismic performance scores defined under the “Principles for the Identification of Risky Structures” using a final dataset of 3,543 buildings, obtained after preprocessing raw data from 4,200 reinforced concrete buildings in central Elazığ. Various supervised machine learning models were compared. Input parameters included building identification data, geometric characteristics, and structural irregularities, while the seismic performance score was the output. Models such as KNN and Random Forest were trained and evaluated using regression metrics including R-squared (R²), mean absolute error (MAE), and mean squared error (MSE). Results indicate that the Random Forest model predicts seismic performance scores with high accuracy. These findings suggest that such approaches can serve as fast, effective, and reliable decision-support tools for post-earthquake building risk prioritization. Additionally, they help reduce time and labor costs in field data collection, contributing to more efficient disaster management and improved urban resilience. The study is expected to support urban transformation and disaster management strategies in earthquake-prone regions like Elazığ.

Keywords

Supporting Institution

This study was supported by the Disaster and Emergency Management Presidency (AFAD) of Turkey under the project numbered UDAP Ç-21-62.

Ethical Statement

The authors declare that they have adhered to all ethical standards. This study is derived from the doctoral dissertation by Rabia Nur SAĞLAM titled “Improving Rapid Risk Assessment Methods in Reinforced Concrete Buildings Using Machine Learning Techniques.”

Thanks

The authors would like to thank the reviewers and the editorial board for their valuable comments and constructive suggestions that helped improve the quality of this manuscript.

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Details

Primary Language

English

Subjects

Architectural Science and Technology, Earthquake Engineering, Structural Engineering

Journal Section

Research Article

Authors

Rabia Nur Sağlam
0000-0003-3015-0766
Türkiye

Muhammed Veysi Güler ^*
0009-0002-8350-9808
Türkiye

Mahmut Kaya
0000-0002-7846-1769
Türkiye

Mustafa Ulaş
0000-0002-0096-9693
Türkiye

Kürşat Esat Alyamaç
0000-0002-3226-4073
Türkiye

Publication Date

June 22, 2026

Submission Date

April 14, 2026

Acceptance Date

June 2, 2026

Published in Issue

Year 2026 Volume: 12 Number: 1

DOI

https://doi.org/10.29132/ijpas.1928087

IZ

https://izlik.org/JA69WA33BA

Cite

RIS / Bibtex

APA

Sağlam, R. N., Güler, M. V., Kaya, M., Ulaş, M., & Alyamaç, K. E. (2026). Seismic performance prediction of reinforced concrete buildings using the RYTEIE method: a comparison of machine learning models. International Journal of Pure and Applied Sciences, 12(1), 406-422. https://doi.org/10.29132/ijpas.1928087

AMA

1.Sağlam RN, Güler MV, Kaya M, Ulaş M, Alyamaç KE. Seismic performance prediction of reinforced concrete buildings using the RYTEIE method: a comparison of machine learning models. International Journal of Pure and Applied Sciences. 2026;12(1):406-422. doi:10.29132/ijpas.1928087

Chicago

Sağlam, Rabia Nur, Muhammed Veysi Güler, Mahmut Kaya, Mustafa Ulaş, and Kürşat Esat Alyamaç. 2026. “Seismic Performance Prediction of Reinforced Concrete Buildings Using the RYTEIE Method: A Comparison of Machine Learning Models”. International Journal of Pure and Applied Sciences 12 (1): 406-22. https://doi.org/10.29132/ijpas.1928087.

EndNote

Sağlam RN, Güler MV, Kaya M, Ulaş M, Alyamaç KE (June 1, 2026) Seismic performance prediction of reinforced concrete buildings using the RYTEIE method: a comparison of machine learning models. International Journal of Pure and Applied Sciences 12 1 406–422.

IEEE

[1]R. N. Sağlam, M. V. Güler, M. Kaya, M. Ulaş, and K. E. Alyamaç, “Seismic performance prediction of reinforced concrete buildings using the RYTEIE method: a comparison of machine learning models”, International Journal of Pure and Applied Sciences, vol. 12, no. 1, pp. 406–422, June 2026, doi: 10.29132/ijpas.1928087.

ISNAD

Sağlam, Rabia Nur - Güler, Muhammed Veysi - Kaya, Mahmut - Ulaş, Mustafa - Alyamaç, Kürşat Esat. “Seismic Performance Prediction of Reinforced Concrete Buildings Using the RYTEIE Method: A Comparison of Machine Learning Models”. International Journal of Pure and Applied Sciences 12/1 (June 1, 2026): 406-422. https://doi.org/10.29132/ijpas.1928087.

JAMA

1.Sağlam RN, Güler MV, Kaya M, Ulaş M, Alyamaç KE. Seismic performance prediction of reinforced concrete buildings using the RYTEIE method: a comparison of machine learning models. International Journal of Pure and Applied Sciences. 2026;12:406–422.

MLA

Sağlam, Rabia Nur, et al. “Seismic Performance Prediction of Reinforced Concrete Buildings Using the RYTEIE Method: A Comparison of Machine Learning Models”. International Journal of Pure and Applied Sciences, vol. 12, no. 1, June 2026, pp. 406-22, doi:10.29132/ijpas.1928087.

Vancouver

1.Rabia Nur Sağlam, Muhammed Veysi Güler, Mahmut Kaya, Mustafa Ulaş, Kürşat Esat Alyamaç. Seismic performance prediction of reinforced concrete buildings using the RYTEIE method: a comparison of machine learning models. International Journal of Pure and Applied Sciences. 2026 Jun. 1;12(1):406-22. doi:10.29132/ijpas.1928087