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:: Volume 6, Issue 3 (10-2016) ::
Disaster Prev. Manag. Know. 2016, 6(3): 284-294 Back to browse issues page
Modeling the amplification of seismic waves with artificial Neural network (Case Study: Urmia City)
Najme Alidadi Miss 1, Abbas Mahdavian Dr.2
1- Shahid Beheshti University,Faculty of Civil, Water and Enviromental Engineering
2- Shahid Beheshti University,Faculty of Civil, Water and Enviromental Engineering
Abstract:   (4368 Views)

Background and objective: Soil effects in seismic design codes is often based on soil type and average shear wave velocity in different layers. In some seismic design codes, some effects such as the effects of thickness and depth of the bedrock seismic structure are ignored. Past earthquakes experience has proved that thickness of soil layers has a significant impact on the earth response and is unavoidably. Since, Iran is located in the seismic belt areas of the world, and Urmia city is also located in a high seismic potential area of Iran, so in this research, the effect of amplifying seismic waves in marl and sandy soils with different thicknesses has been examined in this area.

Methodology: One dimensional analysis of sandy and marl with unequal thicknesses done by considering the place geotechnical characteristics. It is used from artificial accelerograms simulated based on seismic hazard analysis results as input motion of analysis in this analysis. This amplification ratio is modeled by neural network. Artificial neural network model is a new way to create a knowledge system based on collecting sample data.

Finding: Knowledge used in this model is a neural network to predict the seismic response that is mainly based on real data which can be utilized by using this model. In this paper, a model is designed using artificial neural network (ANN) to predict seismic magnification coefficients. The main advantage of this method is high performance in operation and high speed response of structures under Accelerograms be determined.

Conclusion:In this study, the results of artificial neural network using correlation coefficients and root mean square error criteria has been used to offer precise answer and the obtained results can be used in evaluating sand and marl soils in seismic in Urmia city.

Keywords: Equivalent linear analysis, Site effects, Seismic hazard analysis, Amplification ratio, Artificial accelerogram, Artificial Neural network.
Full-Text [PDF 937 kb]   (1122 Downloads)    
Type of Study: ترویجی | Subject: General
Received: 2016/06/1 | Accepted: 2016/08/3 | ePublished: 2016/09/26
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Alidadi N, Mahdavian A. Modeling the amplification of seismic waves with artificial Neural network (Case Study: Urmia City). Disaster Prev. Manag. Know.. 2016; 6 (3) :284-294
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Volume 6, Issue 3 (10-2016) Back to browse issues page
فصلنامه علمی - ترویجی دانش پیشگیری و مدیریت بحران Disaster Prevention and Management Knowledge (quarterly)
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