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中文摘要：
提出一种混合交叉进化算法来估计混沌系统的未知参数.首先通过构造一个适当的适应度函数,将混沌系统的参数估计问题转化为一个多维的优化问题.在混合交叉进化算法中,利用佳点集方法初始化种群,增加了算法的稳定性和全局搜索能力.在进化过程中,混合交叉操作既能指导种群个体向最优解子空间靠近,又能提高算法跳出局部最优的能力,从而协调了算法的勘探和开采能力.以几个标准测试函数和典型的Lorenz混沌系统为例进行仿真实验,结果表明了该方法的有效性.
英文摘要：
A hybrid-crossover-based evolution algorithm is proposed to estimate the parameters of chaotic system.Through establishing an appropriate fitness function,the parameter estimation problem is coverted into a multi-dimensional functional optimization problem. In this approach,the individual generation based on good-point-set method is introduced into the evolutionary algorithm initial step, which reinforces the stability and global exploration ability of the evolutionary algorithm.In the evolution process,it not only can be explored to induce the new individuals generated by stochastic hybrid crossover operation to fly into the better subspace,but also can avoid the premature convergence and speed up the convergence.It coordinates the exploitation ability and the exploration ability of algorithm.Numerical simulations on the benchmark function and the Lorenz system are conducted.The results demonstrate the effectiveness of the proposed algorithm,which is shown to be an effective method of parameter estimation for chaotic systems.
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