片语

genetic triangulation algorithm遗传三角剖分

genetic reduction algorithm遗传约简算法

genetic learning algorithm遗传学习算法

genetic bp algorithm遗传bp算法

genetic programming algorithm gpa遗传程序设计算法

immune genetic annealing algorithm免疫遗传退火算法

Genetic Quantum Algorithm遗传量子算法

genetic scheduling algorithm遗传调度算法

genetic attacking algorithm遗传攻击算法

英汉例句

• the evolutionary genetic algorithm is a fascinating topic that can hardly be exhausted in a single article.

  进化遗传算法是个非常吸引人的话题，在一篇文章中想把所有内容都讲清楚几乎是不可能的。

• emerging in the early 1960s, the genetic algorithm (and evolutionary algorithms in general) took a place in computer science between deterministic and non-deterministic algorithms.

  遗传算法（以及普遍意义上的进化算法）出现在20 世纪 60 年代早期，并在计算机科学的确定性和非确定性算法之间占据了一席之位。

• one program i haven「t written yet, except in a crude prototype, is a graphical version of zlatanov」s genetic algorithm modeler (read about it in his developerworks article listed in resources).

  一个我还没写的程序（虽然我已写了这个程序的原始的原型）是zlatanov 的遗传算法模拟器（请阅读他在developerworks发表的文章中有关这个模拟器的内容，这篇文章被列在 参考资料中。） 的图形版本。

• the perl examples shown here are not as fast as their equivalents in c, but they will show you how the genetic algorithm works, and they are fast enough for some problems.

  本文展示的perl例程不如其c 语言的等价程序快，但是可以使您明白遗传算法是如何工作的，况且，对于一些问题来说，已经够快了。

• the genetic algorithms faq is quite outdated, but it does point to useful suites of genetic algorithm software, both free and commercial.

  遗传算法常见问题解答有些过时，但是它指向的的确是一些有用的遗传算法的软件，有免费的也有商业化的。

• in the resources section, there's a link to mybeasties, an advanced perl module for genetic algorithm applications.

  在 参考资料一节中，有指向mybeasties的链接，这是用于遗传算法应用程序的高级perl模块。

• the fitness formula is the most-used function in the genetic algorithm (it will be invoked (population size) x (generations times)), so you should make it as simple and as fast as possible.

  适应性公式是遗传算法中最常用的函数，（它将要被调用的次数是（人群大小）x（代的数目）次），所以您应当尽可能的使它简单、快速。

• we use genetic algorithm to determine the parameters of controller.

  而控制器的参数则利用遗传算法优化得到。

• the method and the traditional optimization method and the genetic algorithm are compared through the example.

  通过实例的应用将该法与传统优化方法和遗传算法进行了比较。

• if you loosen the rules too much, the individual fitness does not rise steadily as time goes on, making the genetic algorithm useless.

  如果您的规则过于宽松，则个体适应性不会随着时间的推移而稳定地增加，使得遗传算法毫无用处。

• write your own genetic algorithm implementation.

  编写您自己的遗传算法的实现。

• schlumberger, a leading oil and gas exploration company, applies software that generates and analyzes optimal portfolios of exploration projects (oil wells) using a genetic algorithm iteration method.

  一个领先的石油气探测公司，应用那些利用遗传算法迭代方法来生成并分析探测项目（油井）的最优投资组合的软件。

• the genetic algorithm is simple enough for anyone to understand, using biological terms taught in high school.

  遗传算法是如此简单，任何人只要用高中时学过的生物术语就可以理解。

• the result shows that the optimization carried out by adopting genetic algorithm produces a set of results, not just only one.

  结果表明，当评价标準相同时，遗传算法在优化设计中给出的是一组优化结果，而不是唯一的选择；

• in addition, the genetic algorithm is not bound by time.

  另外，遗传算法不受时间限制。