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International Journal of Optimaization in Civil Engineering، جلد ۸، شماره ۱، صفحات ۱۵-۲۸
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عنوان انگلیسی GENERATION OF SYNTHETIC EARTHQUAKE RECORDS BY ARTIFICIAL INTELLIGENCE TECHNIQUES
چکیده انگلیسی مقاله For seismic resistant design of critical structures, a dynamic analysis, based on either response spectrum or time history is frequently required. Due to the lack of recorded data and randomness of earthquake ground motion that might be experienced by the structure under probable future earthquakes, it is usually difficult to obtain recorded data which fit the necessary parameters (e.g. soil type, source mechanism, focal depth, etc.) well. In this paper, a new method for generating artificial earthquake accelerograms from the target earthquake spectrum is suggested based on the use of wavelet analysis and artificial neural networks. This procedure applies the learning capabilities of neural network to expand the knowledge of inverse mapping from the response spectrum to the earthquake accelerogram. At the first step, wavelet analysis is utilized to decompose earthquake accelerogram into several levels, which each of them covers a special range of frequencies. Then for every level, a neural network is trained to learn the relationship between the response spectrum and wavelet coefficients. Finally, the generated accelerogram using inverse discrete wavelet transform is obtained. In order to make earthquake signals compact in the proposed method, the multiplication sample of LPC (Linear predictor coefficients) is used. Some examples are presented to demonstrate the effectiveness of the proposed method.
کلیدواژه‌های انگلیسی مقاله
نویسندگان مقاله m فدوی امیری | m fadavi amiri


سید علی سلیمانی ایوری | s a soleimani eyvari


h حسن پور | h. hasanpoor


m شامخی امیری | m shamekhi amiri


نشانی اینترنتی http://ijoce.iust.ac.ir/browse.php?a_code=A-10-66-164&slc_lang=en&sid=en
فایل مقاله اشکال در دسترسی به فایل - ./files/site1/rds_journals/426/article-426-413565.pdf
کد مقاله (doi)
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده Applications
نوع مقاله منتشر شده پژوهشی
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