ON THE PREDICTION OF STRUCTURAL REACTIONS TO BIG EARTHQUAKES IN TURKEY

Year 2017, , 335 - 340, 30.06.2017

Guvenc Arslan Diaa Fawzy Coskun Atay

https://doi.org/10.17261/Pressacademia.2017.608

Abstract

The
prediction of structural reactions to big earthquakes is vital in giving
warnings for potential damages early enough to minimize losses of life and
properties. In the current study we describe buildings by fixed construction
and environmental related parameters. Our models are based on real data of
damaged buildings collected after the occurrence of three big earthquakes in
Turkey. We extend our previous work to include the soil type for damaged
buildings. We employ different techniques, namely neural networks (NN) and
support vector machines (SVM) to improve the prediction accuracy. The results
show that support vector machines, and in particular support vector regression
gives better results compared to neural networks. Although we only used
averages of soil type for each region, we observed that adding soil type has
improved accuracy of predictions for building damages. It is to be noted that
these types of predictions are important to ensure the serviceability and
safety of existing structures. Our models are vital for the authorities to make
fast and reliable decisions and can be also used to improve the development of
new constructions codes. 

Keywords

earthquakes

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