Robust attenuation relations for peak time-domain parameters of strong ground motions

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Mohammadnejad:2012:EES,

• author = "Ali Kafaei Mohammadnejad and Seyyed Mohammad Mousavi and Mohammad Torabi and Mehdi Mousavi and Amir Hossein Alavi",
• title = "Robust attenuation relations for peak time-domain parameters of strong ground motions",
• journal = "Environmental Earth Sciences",
• year = "2012",
• volume = "67",
• number = "1",
• pages = "53--70",
• month = sep,
• keywords = "genetic algorithms, genetic programming, Time-domain ground-motion parameters, Attenuation relationship, Simulated annealing, Nonlinear modelling",
• publisher = "Springer",
• language = "English",
• ISSN = "1866-6280",
• URL = "http://link.springer.com/article/10.1007%2Fs12665-011-1479-9",
• DOI = "doi:10.1007/s12665-011-1479-9",
• size = "18 pages",
• abstract = "This study presents new attenuation models for the estimation of peak ground acceleration (PGA), peak ground velocity (PGV), and peak ground displacement (PGD) using a hybrid method coupling genetic programming and simulated annealing, called GP/SA. The PGA, PGV, and PGD were formulated in terms of earthquake magnitude, earthquake source to site distance, average shear-wave velocity, and faulting mechanisms. A worldwide database of strong ground motions released by Pacific Earthquake Engineering Research Center (PEER) was employed to establish the models. A traditional genetic programming analysis was performed to benchmark the proposed models. For more validity verification, the GP/SA models were employed to predict the ground-motion parameters of the Iranian plateau earthquakes. Sensitivity and parametric analyses were carried out and discussed. The results show that the GP/SA attenuation models can offer precise and efficient solutions for the prediction of estimates of the peak time-domain characteristics of strong ground motions. The performance of the proposed models is better than or comparable with the attenuation relationships found in the literature.",

}

Genetic Programming entries for Ali Kafaei Mohammadnejad Seyyed Mohammad Mousavi Mohammad Torabi Mehdi Mousavi A H Alavi

Citations