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In recent decades, near fault ground motions has been of great importance due to the difference in characteristics of earthquake records in the regions near to the active faults. Most of the developed control systems for structural vibration control have difficulties in dealing with these kinds of strong ground motions regarding the deficiencies of the human knowledge-based control systems such as fuzzy logic controllers for this purpose. Hence, the optimization of these controllers has been concerned in recent years. The main aim of this paper is to optimize the fuzzy controllers implemented in steel structures with nonlinear behavior in which the arithmetic optimization algorithm (AOA) is utilized as the main optimization algorithm while an improved version of this algorithm as IAOA is also proposed for performance enhancement of the standard algorithm. In the IAOA, a new parameter identification process is proposed in which the Levy flight as a well-known stochastic process with step length determined by levy distribution is implemented in the main loop of the AOA. The IAOA and AOA are utilized for optimization of the membership functions and the rule base of the fuzzy controllers implemented in a large-scale building structure. The overall performance of the IAOA is compared with the standard AOA and other metaheuristics. The obtained results of the improved method demonstrate the capability of this method in providing very competitive solutions which results in decreasing structural responses and damages of the considered building in dealing with the near-fault strong ground motions.
Artificial Intelligence Review – Springer Journals
Published: Jun 1, 2022
Keywords: Improved arithmetic optimization algorithm; Fuzzy logic controller; Near-fault earthquake; Ground motion; Optimization
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