1
Graduate Student, Dept. of Civil Engineering, Faculty of Engineering, Arak University
2
Arak University
Abstract
The main scope of this paper is to study an application of evolutionary algorithms, i.e. genetic algorithm and genetic programming (GP), for obtaining Peak Ground Acceleration (PGA) prediction model in the case of Iranian database. The proposed GP model is compared with a set of existing attenuation relationships via several traditional and modern mathematical and statistical methods. A new re-sampling approach is also introduced to assess the stability of the chosen models. The obtained model shows clearly more consistency with the local data in comparison with the other selected models.
Rahpeyma, S., Azarbakht, A., & Mousavi, M. (2013). A New Peak-Ground-Acceleration Prediction Model by Using Genetic Optimization Techniques for Iranian Plateau Database. Journal of Seismology and Earthquake Engineering, 15(Issue 3 and 4), 153-170.
MLA
Sahar Rahpeyma; Alireza Azarbakht; Mehdi Mousavi. "A New Peak-Ground-Acceleration Prediction Model by Using Genetic Optimization Techniques for Iranian Plateau Database". Journal of Seismology and Earthquake Engineering, 15, Issue 3 and 4, 2013, 153-170.
HARVARD
Rahpeyma, S., Azarbakht, A., Mousavi, M. (2013). 'A New Peak-Ground-Acceleration Prediction Model by Using Genetic Optimization Techniques for Iranian Plateau Database', Journal of Seismology and Earthquake Engineering, 15(Issue 3 and 4), pp. 153-170.
VANCOUVER
Rahpeyma, S., Azarbakht, A., Mousavi, M. A New Peak-Ground-Acceleration Prediction Model by Using Genetic Optimization Techniques for Iranian Plateau Database. Journal of Seismology and Earthquake Engineering, 2013; 15(Issue 3 and 4): 153-170.
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