GENERATION OF ARTIFICAL ACCELEROGRAMS USING NEURAL NETWORKS FOR DATA OF IRAN

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BARGI KH.; RAHAMI H.; LOUX C.

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Journal: Year:2002 | Volume:36 | Issue:2 (76) Page(s): 177-183

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Title

GENERATION OF ARTIFICAL ACCELEROGRAMS USING NEURAL NETWORKS FOR DATA OF IRAN

Author(s)

BARGI KH. | RAHAMI H. | LOUX C. | Issue Writer Certificate

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Abstract

A new method for generation of artificial earthquake accelerograms from response spectra is proposed by Ghaboussi and Lin in 1997 using neural networks. In this paper the methodology has been extended and enhanced for data of Iran. For this purpose, first 40 records of Iran acceleration is chosen, then an RBF neural network which called generalized regression neural network (GRNN) learn the inverse mapping directly from the response spectrum to the Discrete Cosine Transform (DCT) of accelerograms. DCT has been used as an assisting device to extract the content of frequency domain. Learning of network is reasonable and a GRNN learns it in a few second. Outputs are presented to demonstrate the performance of this method and show its capabilities.

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APA: Copy

BARGI, KH., RAHAMI, H., & LOUX, C.. (2002). GENERATION OF ARTIFICAL ACCELEROGRAMS USING NEURAL NETWORKS FOR DATA OF IRAN. JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TEHRAN), 36(2 (76)), 177-183. SID. https://sid.ir/paper/14156/en

Vancouver: Copy

BARGI KH., RAHAMI H., LOUX C.. GENERATION OF ARTIFICAL ACCELEROGRAMS USING NEURAL NETWORKS FOR DATA OF IRAN. JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TEHRAN)[Internet]. 2002;36(2 (76)):177-183. Available from: https://sid.ir/paper/14156/en

IEEE: Copy

KH. BARGI, H. RAHAMI, and C. LOUX, “GENERATION OF ARTIFICAL ACCELEROGRAMS USING NEURAL NETWORKS FOR DATA OF IRAN,” JOURNAL OF FACULTY OF ENGINEERING (UNIVERSITY OF TEHRAN), vol. 36, no. 2 (76), pp. 177–183, 2002, [Online]. Available: https://sid.ir/paper/14156/en

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