算法的

An approach is given to pick out the optimal solution from the set of solutions of the parametric optimization problems.

这种算法为三级算法。本文证明了算法的收敛性并建立了其理论基础，仿真效果好。

Because of its simplicity and applicability, the TSP has for decades served as an initial proving ground for new ideas.

本文以TSP问题作为实验对象，对蚁群算法的一种――相遇算法进行了改进，提出了并行相遇算法。

According to disadvantage of AS that the speed low of convergentiss and easily entering the stagnation,improving the AS in some aspect by the way that importing pheromone windows that the value of pheromone cannot exceed the window,only deposit the pheromone on the edge that belongs to the iteration shortest solution path,releasing additional pheromone to the edge belongs to the so-far shortest solution path,judging the situation of convergent and to reinitialize pheromone,optimizing the solutions by local search procedure at the end of every iteration,modifying the transition probability by add some problem specific parameters and so on.

本文主要运用蚁群优化算法(Ant Colony Optimization，ACO)来求解VRP。针对蚁群算法收敛性比较差，易于停滞的缺陷，通过使用信息素窗口限制、信息素的最大最小值，只更新信息素迭代中最好解，增加了精英的蚂蚁，信息素重新初始化之前先判断出汇聚情况，在每次迭代过程中加入局部的搜索进行优化，在对蚁群算法进行了优化时考虑选择概率当中加入与问题的相关参数等措施，从而使蚁群算法的收敛性得到大大提高，避免了算法的停滞现象。

Simulation results demonstrate that the average one-hop distance is estimated more exactly in the proposed algorithm than that of DV-Hop, the root mean square error is decreased and the location precision is improved.

仿真结果表明，与DV-Hop算法的平均跳距离估计算法相比，本文算法更准确地估计平均跳距离，降低了均方根误差，并提高了定位精度。

Associated with the analysis of the new algorithm in pure coning environment, general expression of rotating vector in the new algorithm is given, and the basic and optimized algorithm of the new coning compensation algorithm are deduced.

在分析经典圆锥运动误差基础上，给出了新算法的旋转矢量通式，并推导了这类圆锥补偿基本算法及其优化算法补偿系数通式。

Numerical results illustrate the effectiveness of the optimized domain decomposition methods we proposed compared with the classical Schwarz methods.

在此基础上考察了古典Schwarz算法和各种优化区域分解算法的收敛性质，验证了优化区域分解算法。

Firstly, the paper expatiates the essence principle of the motion estimation based block matching, introduces Full Search method and several typical motion estimation fast algorithms, and analyzes each characteristic, then to sum up the key technology for increasing the motion estimation search efficiency; Secondly, it stress introduces three motion estimation fast improved algorithms: the improved algorithm based Full Search method, it imports successive elimination algorithm、subsample and termination condition to increase search speed for enhancing the real time of Full Search.

本文首先阐述了基于块匹配法的运动估计基本原理，介绍了全搜索法和几种典型的运动估计快速算法，分析了各算法的特点，在此基础上总结了提高运动估计搜索效率的几个关键技术。接着重点介绍了本文提出的三种运动估计快速改进算法。基于全搜索的改进算法，是在全搜索的基础上尝试引入了连续排除算法、子抽样和终止条件来提高搜索速度，增强全搜索的实时性。

Especially the hybrid particle swarm optimization algorithm with across strategy and mutation strategy is simple and effective.

与模拟退火算法、标准遗传算法进行比较，24种混合粒子群算法的效果都比较好，其中交叉策略D和变异策略F的混合粒子群算法的效果最好，而且简单有效。

The thesis analysises the superiority of genetic algorithm in dealing with discreate variables and primal-dual interior point method in dealing with continuous variables, and brings forward a discoupled combined algorithm which is based on the equipment control priority and take advantage of genetic algorithm and primal-dual interior point method, and the emulator of IEEE-30 bus system validates the fesability of the discoupled combined algorithm.

本文分析了遗传算法在处理离散变量和原对偶内点法处理连续变量的优势，提出一种基于设备动作优先级并利用遗传算法和原对偶内点法的解耦组合算法思路，通过IEEE-30节点系统仿真验证了该解耦组合算法的可行性。

The principle of MUSIC algorithm and theoretical analysis of the spectral separate frequency and frequency detection threshold are included. MUSIC algorithm compared with FFT based algorithm for harmonic frequency estimation using matlab simulation platform .

给出了MUSIC算法的基本原理，对MUSIC算法的频谱分辨能力和频率检测门限进行了理论分析，在Matlab仿真平台下对MUSIC算法和FFT算法的频率估计性能进行了比较。

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。