What is the translation of " GENETIC ALGORITHMS " in Chinese?

• 遗传算法
• 基因算法

Examples of using Genetic algorithms in English and their translations into Chinese

For prediction, I used a technique close to today's genetic algorithms.
为了进行预测，我使用非常接近于目前的遗传算法的方法。

Genetic algorithms are based on the mechanisms of natural selection and genetics.
遗传算法基于自然选择和遗传学机制。

So, while helpful, current genetic algorithms are far from the end of the story.
因此，虽然有用，当前的遗传算法还远远不是故事的结局。

The tools you will use will be TD-Learning, Q-Learning and genetic algorithms.
你将使用的工具将是TD-Learning，Q-Learning和遗传算法。

Like genetic algorithms, Reinforcement Learning is an unsupervised learning problem.
和遗传算法一样，强化学习是一种非监督学习。

The tools you will use will be TD-Learning, Q-Learning and genetic algorithms.
你将使用的工具包括TD-Learning、Q-Learning和遗传算法。

Both hill-climbing and genetic algorithms can be used to learn the best value of x.
爬山算法和遗传算法可以用来学习出x的最优值。

The tools that you would use include TD-Learning, Q-Learning and genetic algorithms.
你将使用的工具包括TD-Learning、Q-Learning和遗传算法。

We tried to come up with a way to use genetic algorithms to create a new type of concentrator.
我们已经用这个基因算法来进行制造新型太阳能收集器的尝试。

Of course, inexpensive microprocessors and then a very important breakthrough-- genetic algorithms.
当然还有较便宜的微处理器和非常重要的突破性技术，那就是基因算法。

Materials by design: Argonne researchers use genetic algorithms for better superconductors.
材料设计：Argonne研究人员使用遗传算法获得更好的超导体。

Evolver's genetic algorithms constantly try new, different solutions to arrive at the best answer possible.
Evolver的遗传算法不断尝试新的不同解法，以生成最佳可能解法。

For more information about applying genetic algorithms, see Global Optimization Toolbox.
有关应用遗传算法的更多信息，请参阅GlobalOptimizationToolbox。

Unlike genetic algorithms, differential evolution carries out operations over each component(or each dimension of the solution).
然而，与遗传算法不同，差分进化对每个组件（或解的每个维度）执行操作。

Projects like[email protected],[email protected] and genetic algorithms can easily be implemented on top of such a platform.
Emailprotected和基因算法这样的项目就很容易在这样的平台上进行。

Conventional genetic algorithms only allow evolution within the narrow confines of a narrow problem, and a single means of evolution.
传统的遗传算法只允许在狭窄问题和单一进化手段的范围内进行进化。

So using that new twist, with the new criteria, we thought we could re-look at the Stirling engine, and also bring genetic algorithms in.
接下来用这个新的标准来重新检视斯特灵机，同时将基因算法引进。

John Holland introduced genetic algorithms in 1960 based on the concept of Darwin's theory of evolution;
JohnHolland在1960年基于达尔文进化论的概念引入了遗传算法;

As a stand-alone task, feature selection can be unsupervised(e.g. Variance Thresholds) or supervised(e.g. Genetic Algorithms).
作为独立的任务，特征选取既可以是非监督式的(如方差阈值)，又可以是监督式的(比遗传算法)。

It may be that as with neural networks, genetic algorithms can be applied to some portion of the pathfinding problem.
也许在和神经网络结合的情况下，遗传算法可以应用于寻路问题的某个部分。

Deb, Multi-objective function optimization using non-dominated sorting genetic algorithms.
Deb在1995年发表的一篇名为《Multiobjectivefunctionoptimizationusingnondominatedsortinggeneticalgorithms.

For the first few decades, the genetic algorithms community consisted mainly of John Holland, his students, and their students.
在开始的几十年，遗传算法的阵营主要由约翰·霍兰德、他的学生、这些学生的学生组成。

But many artificial intelligence programs, such as those using genetic algorithms or deep learning, are not transparent(unless designed to be).
但很多人工智能程序，比如采用遗传算法或深度学习的程序，却并不透明（除非被设计成透明）。

It then used genetic algorithms to iteratively tweak the code until it was able to bypass the defenses while maintaining its function.
然后，它用遗传算法反复修改代码，直到能够绕过防御，同时保持其功能。

However, one can apply reinforcement learning or genetic algorithms in order to build an artificial neural network architecture that one might not have used earlier.
然而，你能用强化学习或遗传算法来构建你以前从没想过要用的人工神经网络结构。

In general, genetic algorithms tend to work better than traditional optimization algorithms because they're less likely to be led astray by local optima.
一般来说，遗传算法往往比传统的优化算法工作得更好，因为它们不太可能被局部Optima引入歧途。

Genetic Algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on bio-inspired operators such as mutation, crossover and selection.
遗传算法通常用于生成高质量的优化和搜索问题的解决方案，依靠生物启发的运算符，如变异，交叉和选择。

In addition, genetic algorithms are population-based and many modern evolutionary algorithms are directly based on, or have strong similarities to, genetic algorithms.
另外，遗传算法是基于群体的，许多现代的进化算法直接基于遗传算法或具有一些强烈的相似性。