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Evaluation of parameters affecting earthquake damage by decision tree techniques

Author

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  • Betül Şengezer
  • Atilla Ansal
  • Ömer Bilen

Abstract

Earthquake damages are assessed based on a holistic approach using structural as well as non-structural factors to model earthquake damage distributions with Decision Tree Techniques, using the Answer Tree program and the damage data from recent major earthquakes in Turkey. The damage dataset consists of approximately 9,400 buildings that were surveyed to evaluate the factors affecting building damage after Erzincan [1992], Dinar [1995], and Kocaeli [1999] earthquakes. The earthquake damage is defined as the dependent variable, while earthquake magnitude (M), intensity (I) in the city, peak ground acceleration (PGA) in each city, epicenter distance (ED), building types (BT), number of storeys (NS), presence of soft storey (SS), building position (BP) on the site, and site conditions (SC) are independent variables in the proposed model. The damage level (DL) was classified with respect to red, yellow, and green codes. The main purpose was (1) to identify the factors controlling building damage during earthquakes; (b) to determine the most significant factor; (c) to evaluate the effects of different factors for different earthquakes; (d) to develop damage distribution models for different subgroups based on the Decision Tree Techniques. Copyright Springer Science+Business Media B.V. 2008

Suggested Citation

  • Betül Şengezer & Atilla Ansal & Ömer Bilen, 2008. "Evaluation of parameters affecting earthquake damage by decision tree techniques," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 47(3), pages 547-568, December.
    • Handle: RePEc:spr:nathaz:v:47:y:2008:i:3:p:547-568
    DOI: 10.1007/s11069-008-9238-2
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    References listed on IDEAS

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    1. Betül Şengezer & Atilla Ansal, 2007. "Probabilistic evaluation of observed earthquake damage data in Turkey," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 40(2), pages 305-326, February.
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    Cited by:

    1. Jihye Han & Soyoung Park & Seongheon Kim & Sanghun Son & Seonghyeok Lee & Jinsoo Kim, 2019. "Performance of Logistic Regression and Support Vector Machines for Seismic Vulnerability Assessment and Mapping: A Case Study of the 12 September 2016 ML5.8 Gyeongju Earthquake, South Korea," Sustainability, MDPI, vol. 11(24), pages 1-19, December.
    2. Ali Shafiee & Mohsen Kamalian & Mohammad Jafari & Hossein Hamzehloo, 2011. "Ground motion studies for microzonation in Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 59(1), pages 481-505, October.
    3. Jihye Han & Jinsoo Kim & Soyoung Park & Sanghun Son & Minji Ryu, 2020. "Seismic Vulnerability Assessment and Mapping of Gyeongju, South Korea Using Frequency Ratio, Decision Tree, and Random Forest," Sustainability, MDPI, vol. 12(18), pages 1-22, September.

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