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Seismic response prediction of isolated buildings based on advanced soft computing method

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Document pages: 12 pages

Abstract: Structural response modeling under seismic load is an important factor in civil engineering, because it has a vital impact on structural design and management, especially in high-risk areas. In this study, the new application of advanced soft computing technology is used to predict the behavior of center supported frame (CBF) buildings with lead rubber bearing (LRB) isolation system under ground motion. These technologies include least squares support vector machine (LSSVM), wavelet neural network (WNN), adaptive neuro fuzzy inference system (ANFIS) and wavelet denoising. This study considers a two-dimensional frame model and eight ground motion simulations to evaluate the prediction model. The comparison results show that the least squares support vector machineor machine is superior to other techniques in estimating the behavior of smart structures.

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