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Real‐time prediction of near‐future seismic excitation adapting AR model to preceding information
Author(s) -
Yamada Kazuhiko
Publication year - 1999
Publication title -
earthquake engineering and structural dynamics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.218
H-Index - 127
eISSN - 1096-9845
pISSN - 0098-8847
DOI - 10.1002/(sici)1096-9845(199912)28:12<1587::aid-eqe883>3.0.co;2-x
Subject(s) - autoregressive model , excitation , identification (biology) , computer science , algorithm , mathematics , engineering , statistics , botany , electrical engineering , biology
This paper examines a real‐time prediction method, aimed at application in active structural control. The examined method applies preceding seismic excitation information at a certain moment to a time‐variant AutoRegressive (AR) model and uses it to predict near‐future excitation information. The performances of this method and appropriate identification parameters are examined by numerical experiments. In fact, the results of these experiments show that a time‐variant AR model with appropriate identification parameters has little change in low‐frequency components despite change in AR coefficients. The performance of a fixed‐coefficient AR model is thus examined. The results show that even a fixed‐coefficient AR model can sufficiently predict 0·05‐s‐future excitation information. Copyright © 1999 John Wiley & Sons Ltd.