A New Peak-Ground-Acceleration Prediction Model by Using Genetic Optimization Techniques for Iranian Plateau Database

Rahpeyma, Sahar; Azarbakht, Alireza; Mousavi, Mehdi

A New Peak-Ground-Acceleration Prediction Model by Using Genetic Optimization Techniques for Iranian Plateau Database

Document Type : Seismology and Engineering Seismology

Authors

Sahar Rahpeyma ¹

Alireza Azarbakht ²

Mehdi Mousavi ²

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.

Keywords

Peak Ground Acceleration (PGA)

Genetic algorithm (GA)

Genetic Programming (GP)

Re-sampling

Iranian Plateau