中文说明：这段代码写为 shuffel 蛙跳算法。SFLA 涉及人口由青蛙一组定义的可能的解决办法。在本文中，我们有 sfla_p 个人。每个代表的功能，每个青蛙子集的青蛙具有最大长度这长度，每个青蛙是不同。分区成多个子集的青蛙的人口被称为 memeplexes。我们创建 sfla_m 个体因此有 sfla_n 中每个个体的青蛙。不同的 memeplexes 被认为是不同文化的青蛙，每个执行本地搜索。在每个个体，还有 submemeplex。在每个 submemeplex sfla_q 青蛙随机选择根据以下的概率函数。Submemeplex 算法不陷入局部最优的原因。
English Description：
this code writed for shuffel frog leaping algorithm. The SFLA involves a population of possible solutions defined by a set of frogs. In this paper we have sfla_p individual. Each frog representing a subset of features .each frog has maximum length this length for each frog is different. Population of frog partitioned into subsets referred to as memeplexes. We create sfla_m memeplex Therefore there are sfla_n frog in each memeplex. The different memeplexes are considered as different cultures of frogs, each performing a local search. Within each memeplex, there is a submemeplex. In each submemeplex there are sfla_q frogs are randomly selected according to Click the file on the left to start the preview,please ！The preview only provides 20% of the code snippets, the complete code needs to be downloaded Loading Report