该算法本质上是一种随机搜索算法，并能以较大概率收敛到全局最优，特别适用于连续函数的优化。
The algorithm is a random searching algorithm in nature. It can converge to the global minima more probability and be adept in continuous functions optimization.
但由于其本质特性，传统遗传算法很容易产生早熟收敛的现象，而不能收敛到全局最优。
But, because of its characteristic, standard GA prematures easily and can't convergence to global optimal.
应用优化算法高度并行、种群个体收敛高度一致的特性，较好的解决了高维统计计算中样本数量与计算时间、样本数量与样本质量之间难以协调的问题。
The problems of harmony between sample number and calculation time, as well as between sample number and sample quality in higher order statistics calculation were achieved.
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