چکیده مقاله
Due to the scarcity of ground motions, it is vital to generate appropriate artificial records in order to perform nonlinear dynamic analysis, particularly in near field regions In this paper a novel methodology is proposed to generate pulse like ground motions The generation process includes simulation of nonpulse type high frequency component of ground motions and directivity pulses separately and then combining them to accomplish final pulse like ground motion Neuro fuzzy networks have been used to produce spectrum compatible nonpulse type ground motions A smoothening approach is taken in order to extract directivity pulses from training records PSO is employed to train Neuro Fuzzy networks using optimized rules and membership functions Wavelet transform is used to decompose accelerograms to special range of frequencies PCA is used as a dimension reduction technique in order to improve training efficiency At the end, an example is provided to show the efficiency of the proposed method
کلیدواژهها
نویسندگان
Saman Eftekhar Ardabili
M Sc Student, Department of Civil Engineering, Ahar Branch, Islamic Azad University, Ahar, Iran
امین قلی زاد
Associate Professor, University of Mohaghegh Ardabili, Ardabil, Iran
شیوه ارجاع
Eftekhar Ardabili, Saman and Gholizad, Amin,1394,Generation of Near-Fault Artificial Records using Artificial Intelligence,10th International Congress on Civil Engineering,Tabriz
ارائهشده در
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