Prediction of peak ground acceleration of Iran's tectonic regions using a hybrid soft computing technique

Geoscience Frontiers

Volumn 7, Issue 1, 2016, Pages 75-82

  Gandomi, Mostafa ^a   Soltanpour, Mohsen ^a   Zolfaghari, Mohammad R ^a   Gandomi, Amir H ^b  

^a K N TOOSI UNIVERSITY OF TECHNOLOGY   (Iran)

^b University of Akron   (United States)

Author keywords

Artificial neural networks; Explicit formulation; Peak ground acceleration; Simulated annealing

Indexed keywords

ARTIFICIAL NEURAL NETWORK; EARTHQUAKE MAGNITUDE; FAULTING; GROUND MOTION; PEAK ACCELERATION; S-WAVE; SEISMIC VELOCITY; SEISMOTECTONICS; SIMULATED ANNEALING; WAVE VELOCITY;

IRAN;

EID: 84955516345     PISSN: 16749871     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.gsf.2014.10.004     Document Type: Article

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