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| Titel |
Ground motion predictive modelling based on genetic algorithms |
| VerfasserIn |
S. Yilmaz |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 11, no. 10 ; Nr. 11, no. 10 (2011-10-20), S.2781-2789 |
| Datensatznummer |
250009732
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| Publikation (Nr.) |
 copernicus.org/nhess-11-2781-2011.pdf |
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| Zusammenfassung |
| This study aims to utilise genetic algorithms for the estimation of peak
ground accelerations (PGA). A case study is carried out for the earthquake
data from south-west Turkey. The input parameters used for the development
of attenuation relationship are magnitude, depth of earthquake, epicentral
distance, average shear wave velocity and slope height of the site.
Earthquake database compiled by the Earthquake Research Institute of Turkey was
used for model development. An important contribution to this study is the
slope/hill data included into the dataset. Developed empirical model has
a good correlation (R = 0.78 and 0.75 for the training and overall datasets)
between measured and estimated PGA values. The proposed model is also
compared with local empirical predictive models and its results are found to
be reasonable. The slope-hill effect found to be an important parameter
for the estimation of PGA. |
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