遗传算法(GA)是模拟自然界生物进化机制的计算模型，是一种全局优化搜索方法。
As a global optimized search means, Genetic Algorithms (GA) are computational models simulating the evolutionary mechanism of nature.
遗传算法作为一种新的全局优化搜索方法，具有智能性搜索、并行式计算、鲁棒性强、应用范围广等优点。
As a new type of searching method for global optimization, Genetic algorithms has some merits such as intelligence searching, parallel mode, robust and wide application.
对于两种PID控制策略来说，最关键的部分在于如何优化控制器参数，在本文中我们采用了遗传算法这一新型的优化搜索方法，并取得了较好的效果。
For two kinds of PID controller, we know how to optimize parameter is a key problem. In this paper, we select the Genetic Algorithms as a search way and get good effect.
对于搜索引擎优化，请考虑可确保针对尽可能多的目录页面建立索引的自底向上的方法。
For search engine optimization, consider the bottom-up approach where you ensure that as many of your catalog pages are indexed as possible.
搜索优化是一个针对你网上的成功的长期的方法。
Search Optimization is a long term approach to your online success.
现在，我们来优化链表中的搜索元素—即find方法。
Now, let's move on to optimizing search elements in the list-that is, the find method. Here are a few potential situations that may occur.
你不能用搜索引擎优化的方法——购买关键词以及影响你的排名，来提高你的酒店在TripAdvisor上的排名。
You can't approach improving TripAdvisor ranking as you might search engine optimization, where you can purchase keywords and impact your listings.
有时作为搜索引擎优化的一个快速方法- - -大量地提交，是最无用的并且很可能不会实现你的目的。
Mass submissions, which are sometimes offered as a quick work-around SEO method, are mostly useless and not likely to serve your purposes.
但是用户习惯的改变并不一定能在数据中得到体现。搜索引擎优化行业也许需要改变一下他们的工作方法了。
But changes in behavior - and ways SEO professionals might want to consider changing their methods - wouldn't necessarily have been reflected in this data.
进化计算是基于遗传学和自然演化思想的一个解决优化、搜索和学习问题的有效方法。
Evolutionary computation is an effective method to solve optimization, search and learning problems, inspired by genetics and nature evolution.
基于混沌运动的初值敏感性和对混沌优化搜索过程的分析，提出了并行自适应混沌优化方法。
Based on the initial value sensitivity of chaotic motion and the analysis of optimal searching process, a parallel adaptive chaotic optimization (PACO) method is proposed.
该方法给出冲突矩阵表示对象流入流水线的限制，通过启发式搜索寻找面向目标优化的调度策略。
The method gives out the presentation be constrained to objects into pipeline by using collision matrix, and findsout scheduling model with goal-oriented optimization by heuristic search.
本文提出一类求解无约束优化问题的非单调曲线搜索方法，在较弱条件下证明了其收敛性。
This paper presents a non-monotone curve search method for unconstrained optimization problems and proves its convergence under some mild conditions.
优化结果说明在这个例子中粒子群优化有更好的表现，这也说明两种方法在问题的多维空间中搜索最优解的方式不同。
The result shows that particle swarm optimization performs better in this case, which implies that the two methods traverse the problem hyperspace differently.
传统的最优化技术大多是基于梯度寻优技术或随机搜索的方法。
Traditional optimization techniques search for the best solutions using gradients or random searching.
采用编码技术、三维搜索方法等解决了相似方案检索和纸箱优化设计问题。
Similar scheme searching and optimum design of cartons are solved by code method and three-dimensional search method.
算例表明，当混沌搜索的次数达到一定数量时，混合优化方法可以保证算法收敛到全局最优解，且计算效率比混沌优化方法有很大提高。
Numerical examples illustrate that the present method possesses both good capability to search global optima and far higher convergence speed than that of chaos optimization method.
将基于直接搜索法的随机全局优化方法用于求解该问题的全局最优解，给出了具体的算法步骤。
A stochastic global optimization method based on direct search is introduced to solve the global optimal solution of the problem, and the process is also discussed in detail.
分析了BP神经网络和混沌优化的特点，并将混沌优化方法和梯度下降法结合起来构成一种新的组合搜索优化方法。
The characteristics of BP neural network and chaos optimal method are analyzed. By integrating chaos optimal method with gradient-decline method, an optimal method of combination search is created.
分析了BP神经网络和混沌优化的特点，并将混沌优化方法和梯度下降法结合起来构成一种新的组合搜索优化方法。
The characteristics of BP neural network and chaos optimal method are analyzed. By integrating chaos optimal method with gradient-decline method, an optimal method of combination search is created.
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