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Determining Parameters in the Phase-Space Reconstruction of Multivariate Time Series on Genetic Algorithm

机译:遗传算法确定多元时间序列相空间重构中的参数

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Based the principle of minimizing average prediction error, in this paper genetic algorithm is adopted to determine parameters in the phase-space reconstruction of multivariate time series. First, the methods of phase-space reconstruction and multivariate time series prediction are introduced. Then the theory of genetic algorithm to select reconstruction parameters is given that chromosome coding is multi-parameters cascade binary string, fitness is average prediction error function and the optimal parameters combination is obtained through genetic operation. Finally, in Matlab2009b simulation environment, the algorithm is applied to confirm embedding dimensions and time-delays of Rossler coupling system, and the results show that the algorithm has high prediction precision and rapid calculating speed.
机译:基于最小化平均预测误差的原理,本文采用遗传算法确定多元时间序列相空间重构中的参数。首先,介绍了相空间重构和多元时间序列预测的方法。然后给出了遗传算法选择重构参数的理论,即染色体编码为多参数级联二进制串,适应度为平均预测误差函数,通过遗传运算得到最优的参数组合。最后,在Matlab2009b仿真环境中,将该算法用于确定Rossler耦合系统的嵌入维数和时延,结果表明该算法具有较高的预测精度和较快的计算速度。

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