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首页> 外文期刊>Nonlinear dynamics >Parameter estimation of unknown fractional-order memristor-based chaotic systems by a hybrid artificial bee colony algorithm combined with differential evolution
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Parameter estimation of unknown fractional-order memristor-based chaotic systems by a hybrid artificial bee colony algorithm combined with differential evolution

机译:混合人工蜂群算法与差分进化相结合的未知分数阶忆阻器混沌系统参数估计

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摘要

In this paper, parameter estimation of unknown fractional-order memristor-based chaotic systems is concerned. Firstly, the parameter estimation is transformed into a multi-dimensional optimization problem, where the fractional orders are treated as independent variables. Then, a hybrid artificial bee colony algorithm combined with differential evolution and other searching mechanisms is put forward to solve the optimization problem. Finally, to demonstrate the effectiveness of the proposed method, numerical simulations based on two typical fractional-order memristor-based chaotic systems are conducted. The simulation results shows that the proposed approach for parameter estimation of unknown chaotic systems is a successful and promising method with higher calculation accuracy, faster convergence speed, and stronger robustness.
机译:本文研究了基于未知分数阶忆阻器的混沌系统的参数估计。首先,参数估计被转化为多维优化问题,其中分数阶被视为自变量。然后,提出了一种结合差分进化和其他搜索机制的混合人工蜂群算法来解决优化问题。最后,为了证明所提方法的有效性,基于两个典型的基于分数阶忆阻器的混沌系统进行了数值模拟。仿真结果表明,所提出的未知混沌系统参数估计方法是一种成功且有希望的方法,具有较高的计算精度,较快的收敛速度和较强的鲁棒性。

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