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Information Journal Paper

Title

PRODUCTION OF SYNTHETIC SEISMIC RECORDS USING FUZZY NEURAL NETWORK

Pages

  65-77

Abstract

 There is a growing need for dynamic time history analysis and the absence of proper records in different areas has necessitated the production of artificiall accelerograms compatible with the whole plan. This study presents a new approach based on wavelet packet transform and artificial intelligence techniques to produce artificial earthquake accelerograms compatible with the whole plan. This approach takes into account the magnitude and the distance from the fault. The study of neural networks and fuzzy WAVELET PACKET ANALYSIS has been used to achieve the desired goal. To do so, first earthquake accelerograms have been collected according to specific site conditions, earthquake magnitude and distance from origin. Then all records have been gatehered for training with fuzzy neural network. Attenuation spectra have been developed on the basis of information in the area using nonlinear regression. Then using fuzzy neural networks, the relationship between earthquake records and the devloped spectra from each record is calculated. In this satge, using WAVELET PACKET ANALYSIS, mapping acceleration are analyzed and converted in to accelerograms (wavelet coefficients).

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  • Cite

    APA: Copy

    SHADMAN HEIDARI, PEYMAN, KHORASANI, MOHAMMAD, & AMRII, MEHDI. (2016). PRODUCTION OF SYNTHETIC SEISMIC RECORDS USING FUZZY NEURAL NETWORK. JOURNAL OF STRUCTURAL ENGINEERING, 12(4 ), 65-77. SID. https://sid.ir/paper/400073/en

    Vancouver: Copy

    SHADMAN HEIDARI PEYMAN, KHORASANI MOHAMMAD, AMRII MEHDI. PRODUCTION OF SYNTHETIC SEISMIC RECORDS USING FUZZY NEURAL NETWORK. JOURNAL OF STRUCTURAL ENGINEERING[Internet]. 2016;12(4 ):65-77. Available from: https://sid.ir/paper/400073/en

    IEEE: Copy

    PEYMAN SHADMAN HEIDARI, MOHAMMAD KHORASANI, and MEHDI AMRII, “PRODUCTION OF SYNTHETIC SEISMIC RECORDS USING FUZZY NEURAL NETWORK,” JOURNAL OF STRUCTURAL ENGINEERING, vol. 12, no. 4 , pp. 65–77, 2016, [Online]. Available: https://sid.ir/paper/400073/en

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