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Optimal seismic design of steel structures by an efficient soft computing based algorithm
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DOI：10.1016/j.jcsr.2009.07.006.png)
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Abstract
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The main aim of this study is to propose advanced soft computing techniques for the optimal seismic design of real steel structures subjected to natural ground motion records. For the solution of the optimization problem an efficient combination of the particle swarm optimization (PSO) and adaptive virtual sub-population (AVSP) algorithms is proposed. Also an efficient combination of the adaptive neuro-fuzzy inference system (ANFIS), wavelet transforms (WT) and radial basis function (RBF) neural networks, termed as fuzzy wavelet radial basis function (FWRBF), is proposed to accurately predict the structural responses. The numerical results demonstrate the computational advantages of the proposed methodology. (C) 2009 Elsevier Ltd. All rights reserved.
Keywords:
Seismic loading
Particle swarm optimization
Adaptive virtual sub-population
Adaptive neuro-fuzzy inference system
Wavelet
Radial basis function neural network
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