问题描述
什么是交叉概率&遗传算法或遗传规划中的变异概率?有人可以从实现的角度来解释它们！
What is Crossover Probability & Mutation Probability in Genetic Algorithm or Genetic Programming ? Could someone explain them from implementation perspective!
推荐答案
突变概率(或比率)基本上是对染色体上随机元素将被翻转成其他东西的相似程度的度量.例如，如果您的染色体被编码为长度为100的二进制字符串(如果您具有1％的突变概率)，则意味着随机选择的100位(平均)中的1位将被翻转.
Mutation probability (or ratio) is basically a measure of the likeness that random elements of your chromosome will be flipped into something else. For example if your chromosome is encoded as a binary string of lenght 100 if you have 1% mutation probability it means that 1 out of your 100 bits (on average) picked at random will be flipped.
交叉基本上模拟了有性基因重组(如在人类生殖中一样)，并且遗传算法通常采用多种方法.有时在遗传算法中以适度的方式应用交叉(因为它打破了对称性，这并不总是很好，而且您也可能会盲目)，因此我们谈论交叉概率来表示将有多少对夫妇的比率被选择进行交配(通常按照选择标准来选择-但这是另一回事了.)
Crossover basically simulates sexual genetic recombination (as in human reproduction) and there are a number of ways it is usually implemented in GAs. Sometimes crossover is applied with moderation in GAs (as it breaks symmetry, which is not always good, and you could also go blind) so we talk about crossover probability to indicate a ratio of how many couples will be picked for mating (they are usually picked by following selection criteria - but that's another story).
这是个短篇小说-如果您想要长篇小说，则必须努力并按照Amber发布的链接进行操作.或做些谷歌搜索-我上次检查还是一个不错的选择:)
This is the short story - if you want the long one you'll have to make an effort and follow the link Amber posted. Or do some googling - which last time I checked was still a good option too :)
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