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Parameter Estimation of Chaotic Systems Using Fireworks Algorithm

机译:基于Fireworks算法的混沌系统参数估计。

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摘要

Chaotic system is a nonlinear deterministic system, and parameter identification for the chaotic system is an important issue in nonlinear science, such as secure communication, etc. By setting up an appropriate objective function, the parameter identification can be converted into a multi-dimensional optimization problem which can be solved by evolutionary algorithms. Emerging as an evolutionary algorithm, Fireworks Algorithm (FWA) has shown its good computational performance and robustness. In order to expand the application of FWA, several types of FWA are applied to estimate the parameters for two typical chaotic systems in which three parameters are totally unknown, simulation results show most of FWAs can have better estimation precision and robustness, and FWA is a new effective parameter identification method for the chaotic systems.
机译:混沌系统是一种非线性确定性系统,混沌系统的参数识别是非线性科学中的重要问题,例如安全通信等。通过建立适当的目标函数,可以将参数识别转换为多维优化进化算法可以解决的问题。作为一种进化算法,Fireworks算法(FWA)表现出了良好的计算性能和鲁棒性。为了扩大FWA的应用范围,应用了几种FWA来估计两个完全未知的两个典型混沌系统的参数,仿真结果表明,大多数FWA都具有较好的估计精度和鲁棒性,FWA为新的混沌系统有效参数识别方法。

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  • 会议地点 Beijing(CN)
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    Air Force Engineering University, Xi'an 710051, China,Department of Intelligence, Air Force Early-Warning Academy, Wuhan 430019, China;

    Air Force Engineering University, Xi'an 710051, China;

    Air Force Engineering University, Xi'an 710051, China;

    Air Force Engineering University, Xi'an 710051, China;

    Department of Intelligence, Air Force Early-Warning Academy, Wuhan 430019, China;

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