Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Evaluation of Multivariate Adaptive Regression Splines for Prediction of Kappa Factor in Western Türkiye
Date
2024-01-01
Author
KURTULMUŞ, TEVFİK ÖZGÜR
Yerlikaya-Ozkurt, F.
Askan Gündoğan, Ayşegül
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
37
views
0
downloads
Cite This
The recent seismic activity on the west coast of Türkiye, including the Aegean Sea region, indicates that a closer focus is necessary on this region. Located in an active tectonic regime of north–south extension with multiple basins on soft soil deposits, the region has a high seismic hazard. Recently, as a combination of basin effects and building vulnerability, the October 30, 2020, Samos event (Mw = 7.0) caused localized significant damage and collapse in İzmir city center despite the 70 km distance from the earthquake source. In spite of this activity, studies on site characterization and site response modeling, including local velocity models and kappa estimates, are still limited in this region. Kappa values exhibit regional characteristics, which necessitates local kappa estimates from past earthquake data for use in region-specific applications. To make the prediction, we used three-component strong ground motion records from accelerometer stations with known VS30 values in western Türkiye that are a part of the Disaster and Emergency Management Presidency’s Turkish National Strong Ground Motion Observation Network. Multiple linear regression (MLR) and multivariate adaptive regression splines (MARS) algorithms have been implemented to build the prediction model. Three factors, such as distance, magnitude, and site class, are included in the kappa evaluation process. The performance of the models in kappa evaluation is calculated based on well-known accuracy measures. The MARS model showed better performance compared to MLR over the selected sites concerning all performance measures. This finding may challenge the most commonly assumed linear models of kappa in the literature.
Subject Keywords
High-frequency attenuation-kappa (κ)
,
Multiple linear regression (MLR)
,
Multivariate adaptive regression splines (MARS)
,
Western Türkiye
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85197367239&origin=inward
https://hdl.handle.net/11511/110196
DOI
https://doi.org/10.1007/978-3-031-57357-6_13
Conference Name
7th International Conference on Earthquake Engineering and Seismology, ICEES 2023
Collections
Department of Civil Engineering, Conference / Seminar
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
T. Ö. KURTULMUŞ, F. Yerlikaya-Ozkurt, and A. Askan Gündoğan, “Evaluation of Multivariate Adaptive Regression Splines for Prediction of Kappa Factor in Western Türkiye,” Antalya, Türkiye, 2024, vol. 401 LNCE, Accessed: 00, 2024. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85197367239&origin=inward.