• generation of near-fault artificial records using artificial intelligence

    جزئیات بیشتر مقاله
    • تاریخ ارائه: 1393/11/01
    • تاریخ انتشار در تی پی بین: 1393/11/01
    • تعداد بازدید: 680
    • تعداد پرسش و پاسخ ها: 0
    • شماره تماس دبیرخانه رویداد: -
     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.

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