Multi-step prediction of strong earthquake ground motions and seismic responses of SDOF systems based on EMD-ELM method |
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| Institution: | 1. Engineering & Computing Building, Faculty of Engineering, Environment and Computing, Coventry University, 3, Gulson Road, Coventry, CV1 2JH, United Kingdom;2. Solid Earth Physics Institute, Faculty of Physics, National and Kapodistrian University of Athens, Panepistimiopolis, Zografos, 157 84 Athens, Greece |
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| Abstract: | This paper proposes a new multi-step prediction method of EMD-ELM (empirical mode decomposition-extreme learning machine) to achieve the short-term prediction of strong earthquake ground motions. Firstly, the acceleration time histories of near-fault ground motions with nonstationary property are decomposed into several components of intrinsic mode functions (IMFs) with different characteristic scales by the technique of EMD. Subsequently, the ELM method is utilized to predict the IMF components. Moreover, the predicted values of each IMF component are superimposed, and the short-term prediction of ground motions is attained with low error. The predicted results of near-fault acceleration records demonstrate that the EMD-ELM method can realize multi-step prediction of acceleration records with relatively high accuracy. Finally, the elastic and inelastic acceleration, velocity and displacement responses of single degree of freedom (SDOF) systems are also predicted with satisfactory accuracy by EMD-ELM method. |
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| Keywords: | Earthquake ground motions Time series prediction Multi-step prediction Empirical mode decomposition Extreme learning machine Seismic responses of SDOF systems |
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