Attenuation relationships of Arias intensity for Iranian plateau using intelligent Gene Expression Programming
The earthquake is one of the natural hazards that have caused many casualties and financial losses throughout the world over the years. This has been the reason why the earthquake hazard analysis studies should be studied more seriously. Iran is also located in one of the seismically active regions...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | FA |
| Publicado: |
Iranian Society of Structrual Engineering (ISSE)
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/cfb6b62138c8405cb3cd6e02425457b1 |
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| Sumario: | The earthquake is one of the natural hazards that have caused many casualties and financial losses throughout the world over the years. This has been the reason why the earthquake hazard analysis studies should be studied more seriously. Iran is also located in one of the seismically active regions of the world, the Himalayan- Alpine belt, which experiences many earthquakes every year. The Arias intensity function, as one of the important earthquake strong motion parameters, contributes greatly to the analysis of seismic hazard, which can be used to estimate the stability of slopes during the earthquake. The purpose of this research is to develop a new attenuation relationship for Arias intensity function in the Iranian plateau using intelligent methods. In this research, 1012 strong motion data were used. Initially, the data required to be filtered were corrected and then all data was analyzed. In this study, parameters such as magnitude of earthquake, focal depth, shear wave velocity and geographic position of the region were used as a variable for the attenuation relationship. Moment magnitude (Mw) was used as earthquake magnitude and earthquakes with magnitudes of above 4 were used in this research. The geographic location of Iran was divided into two regions of Central Alborz and the Zagros region. Gene Expression Programming (GEP), a kind of intelligent algorithm, was used as a method for regression and calculation of the objective function. The advantage of this method is that at first the model for the objective function is not specified and the model is presented optimally by the intelligent method. The fitness function is also defined based on the root least squared error (RMSE). Finally, the attenuation relation based on this fitness function was calculated and the observed results have a high fitness. |
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