并行算法

In order to improve the simulation efficiency, the algorithms are built on binary trees rather than traditional sequent arrays.

算法层面，本文提出了一种基于二叉树的L系统并行重写算法。

In addition, the new compression method is simple, and the memory requirement in the operation process is lower, and it is fit for parallel optimizing progress. The compression speed can be advanced by using DSP, and it also can be implement image real time compression with little information loses.

另外，该压缩方法运算过程中所需存储量小和算法简单的特点，适宜硬件实现，而且便于并行处理，如果用数字信号处理器实现压缩算法，可进一步提高压缩速度，实现用于图像数据在高保真情况下的实时压缩。

It realizes high-speed and selective action without the dependence on the submaster station, and shows more advantages than the centralized protection.

本文研究了几种当前流行的对等式通信方案，并对它们的可行性进行了比较。作者提出了网络式配电网保护的原理和逻辑算法，论证了算法的正确性，分别探讨了当配电网处于辐射状运行方式下和处于多电源并行供电方式下网络式保护的实现方案，并且在现有的硬件平台上进行了网络式保护控制装置的软件设计。

Target model of subtask scheduling is established to minimize the overall time of execution.

建立了设计子任务调度的目标模型，提出了一种针对并行设计子任务调度的遗传算法应用结果表明，在满足子任务间偏序关系条件下，文中算法能够得到设计子任务的最优调度方

The proposed algorithm consists of an n-bit parallel subtracter, an n-bit parallel searcher, and other four sub-procedures.

算法由n位并行减法器、n位数据搜索器和其他4个子算法组成。

The ant colony algorithm is a kind of random search method that developed by coping the natural ant behavior, because of the characters of the characters of running impliedly side by side and searching overall, it makes ACA have advantage that other routine optimization algorithms cant own.

蚁群算法是模仿自然界的蚂蚁行为而发展起来的一种随机搜索方法，由于其隐含并行性和全局搜索特性，使其具有其他常规优化算法无法拥有的优点。

Genetic algorithm is a all-purpose global search method, it will consume seriously the computational resource and computational time, Since traditional genetic algorithm can't make use of the computational resource of multi-core computer fully, it has great practical significance to parallelize genetic algorithm on multi-core CPU.

遗传算法是一种具有很强通用性的全局搜索方法，也是一种计算量大、极耗计算资源的算法，其传统的串行计算形式并不能充分利用多核的计算资源，将其设计为适应多核CPU环境的并行计算形式，具有重要的现实意义。

Thismethod can resolve the near-far problem, and make the system need lower request forthe power control. So we can utilize the uplink frequency spectrum resourcesefficiently and enlarge the system capacity saliently. In 1995, Eberhart and Kennedy reported that the particle swarm optimization algorithm was a parallel optimization.

粒子群优化算法是1995 年由美国的Eberhart 和Kennedy 提出的是一种高效的并行优化算法，简单容易实现同时又有深刻的智能背景，一经提出立刻引起了演化计算等领域的学者们的广泛关注，并在短短几年时间里出现大量的研究成果形成了一个研究热点。

The model provides a bridge between STAP algorithms and real parallel systems. Moreover, it can be applied to performance evaluation.

该模型可以弥补STAP算法和实际并行系统的差距，为开发提供了统一框架；同时，方便了对算法的性能评估。

Based on the study on the traveling salesman problem, in this dissertation, some results on the solving of production scheduling problem using the neural networks are described, which includes the following main parts: l The method which was put forward by Hopfield－Tank of solving the traveling salesman problem is analyzed, and the drawbacks of the method are pointed out. The interlinks between optimal tours and city distribution in the clustering and divide and conquer method are analyzed. A parallel network algorithm on the problem of the traveling salesman problem is presented.

主要包括以下几个方面的内容： 1对Hopfield和Tank提出的解决旅行商问题的方法做了分析和研究，指出该方法的严重不足；对于用聚类方法和各个击破的思想解旅行商问题，分析了最优路径与城市分布之间的几个关系；提出了一个解决旅行商问题的并行网络算法，由这一算法得到的解是&or-optimal&路径。

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。