算法的

Traditionally,this Textbook,including the pretiminaries,introduces algorithmic conception,three algorithmic formtions such as literal language,framework and progrmming wording,and algorithmic optimum.

介绍了算法的概念和自然语言、框图、程序语句3种算法表现形式，以及算法优化问题。

This method is used extensive in the Pattern Recognition,Approximation of Function etc.

本文选取了两种算法中具有代表性BP算法和SVM来阐述优化算法的具体实现和应用。

The paper provides a discarding connection management algorithm, which discards the redundant connection by computation and ensures the maximal attainability of message simultaneously.

该解决方案由丢弃连接管理算法(discarding connection management algorithm，简称DCMA)实现，还给出了算法实例和对算法的讨论。

Combine the advantage of immune clone algorithm and imitate anneal algorithm, put forward task of a kind of reseau to attemper optimize model and algorithm.

结合免疫克隆算法和模拟退火算法的优点，提出了一种网格任务调度优化模型和算法。

This conclusion can also be proved by spectrum-warping audio watermarking algorithm in MCLT domain. To discuss further deeply on why spectrum-warping technique does not have the required robustness, the studies are carried out upon the essentials of bilinear transformation. All the theoretical analysis and experiments results put the robustness of the spectrum-warping audio watermarking under questioning.

四、提出了基于量化的变换域音频水印算法中关于量化参数的选择方法量化变换系数的音频水印算法是以修改谱分量幅值为基础，算法的主要问题是如何选择量化参数以确保算法的鲁棒性和不可感知性，另外量化系数的区域选择也会影响算法的性能。

By comparing the results of BootStrap method with those of BP algorithm it was elucidated that BootStrap is applicable.

通过BootStrap算法与BP算法的预报偏差平方和比较说明BootStrap算法提高了预报精度。

In this article, we implement the other two algorithms, the inverse additive algorithm and the forwards compositional algorithm.

在本文中，我们实施其他两种算法的逆算法和添加剂成分转发算法。

In the paper we analyze and realize using MATLAB two inversion techniques (the gradient method and the DFP method), and check the two techniques , too.

本文分析并用MATLAB实现了两种反演算法，并对这两种算法进行了验模，以评定算法的准确性。

A combination algorithm of discrete particle swarm optimization algorithm and ant colony algorithm for grid resource allocation is presented.

提出一种融合离散粒子群优化算法和蚁群算法的新型算法来解决网格资源分配问题。

The result shows that the method is effective in improving the computational convergence and overcoming the premature of simple genetic algorithm in some degree.

结果表明，自适应遗传算法在保持简单遗传算法优点的同时，有效地提高了算法的收敛性，并在一定程度上克服了简单遗传算法的早熟问题。

The split between the two groups can hardly be papered over.

这两个团体间的分歧难以掩饰。

This approach not only encourages a greater number of responses, but minimizes the likelihood of stale groupthink.

这种做法不仅鼓励了更多的反应，而且减少跟风的可能性。