算法

A new heuristic solution algorithm is presented using an improved genetic algorithm. In the improved genetic algorithm, nondifferentiable exact penalty functions are used to transform a constrained optimization problem into a single unconstrained optimization problem, and hybrid crossovers and intermittent are applied to increase the search capability.

设计了基于改进遗传算法的启发式求解算法，该算法借助不可微精确罚函数将约束问题转化为单个无约束问题来解决，采用混合杂交和间歇变异提高算法的搜索能力。

There exits several MDO algorithms. But they are in our opinion either nonefficient or complicated. So we devised an algorithm called Subspace Approximation Optimization . In the SAO algorithm, the whole system is decomposed into one system-level optimization and several disciplinary optimizations so that a large and complicated problem can be divided into several easy-solving sub-problems. The coupling relationships and the coordination among disciplines are presented by equality constraints and these equality constraints are assigned to relevant disciplines. The optimums of design variables in system level optimization are transferred to discipline level optimization. The optimums of design variables in discipline level correspond to the point that is the nearest to the optimums of design variables in system level. If the optimums of design variables in system level are out of feasible region of discipline 1eve1, linear constraints can be built in the system level optimization using the design variable optimums obtained by the discipline level optimization. The system level optimization would improve the design of the whole system with these linear constraints.

目前，国内外已经发展出了多种飞机多学科设计优化算法，本文的重点是针对协同优化算法的不足，提出了子空间近似优化算法(Subspace ApproximatingOptimization，SAO)，SAO算法中，整个系统的优化问题被分解成一个系统级优化和若干学科级优化，而各个学科之间的耦合与权衡关系则被当作等式约束，这些等式约束将被分配到各个学科级优化中去，系统级优化的任务是寻找整个系统的最优解，而学科级优化的目标函数是以系统级优化分配下来的设计点为圆心的超球半径的平方，因此，如果系统级优化分配下来的设计点在学科级优化可行域内，则学科级优化目标函数为0，反之，则学科级优化的最优点是系统级优化当前设计点距离可行域最近的点。

The multiresolution time-domain algorithm based on the scaling function of the Daubechies wavelet is introduced, and the perfectly matched layer absorbing boundary condition for the algorithm is deduced. In order to overcome the difficulties due to the nonlocalized property of the MRTD basis functions, the pure scattered-field formulation is adopted. The method presented is applied to the scattering analysis of multiple conducting objects, and the numerical results are compared with those by the traditional finite-difference time-domain method. It is shown that the computational resource is reduced drastically without sacrificing much accuracy.

对基于Daubechies小波尺度函数的时域多分辨分析算法进行了详细论述，推导了MRTD算法的完全匹配层吸收边界条件，为克服传统MRTD方法中基函数存在着非局部性的缺点，在源的加入上采用了纯散射场方法；并应用该算法对多目标的电磁散射特性进行了分析，数值结果表明，MRTD算法与传统的时域有限差分法结果相吻合，大大节约了计算资源。

The results show that the learning algorithm of FNN based on PSO is superior to the BP algorithm observably. The PSO algorithm has a good application in neural networks.

研究表明，PSO算法在前向神经网络权值的学习算法中其所有的性能指标均优于传统的BP算法，PSO算法在神经网络的应用中具有广阔的前景。

After carefully analyzed the principle of standard SVPWM and traditional overmodulation methods, this paper proposed one simple and effective overmodulation scheme. Experiments were carried out in one 1.5kW induction motor and its results were recorded and analyzed by PZ4000 Power Analyzer and the proposed scheme were proved to be effective.

在分析了标准SVPWM算法和常见各种过调算法的原理的基础上，提出了一种简单有效的算法满足过调控制的要求，在1.5kW异步电机上进行了实验并使用PZ4000功率分析仪对其结果进行了准确测量与分析，证明了本文提出的SVPWM算法可以有效地提高电源电压的利用率。

In order to study these algorithms systematically and deeply, they are reviewed in this paper based on c-means algorithm, from metrics, entropy, and constraints on membership function or cluster centers. Moreover, the advantages and disadvantages of the typical fuzzy partitional algorithms are discussed.

为了能更为系统和深入地了解这些聚类算法及其性质，本文从改变度量方式、改变约束条件、在目标函数中引入熵以及考虑对聚类中心进行约束等几个方面，对在C-均值算法的基础上得到的基于划分的模糊聚类算法作了综述和评价，对各典型算法的优缺点进行了实验比较分析。

Simulation results show that the proposed method has good performance in time delay predictation of networked control systems, and the plant output can trace desired output effectively.(2)By combining node buffer queuing management and adaptive predictive control, a novel approach on predictive control of NCS is proposed.

在本方法中，使用了直接辨识控制器参数的自适应预测控制算法，该算法不需要在线求解Diophantine方程，减少了计算时间，较好地保证了NCS的实时性；在此基础上，又进一步提出了一种改进型的自适应预测控制算法，不仅避免了在线求解Diophantine方程，并且也不需要进行矩阵求逆运算，使算法的实时性大大提高。

We can also achieve many other new SAs by extending ISP. These new SAs include a multicast algorithm—EISP, a priority algorithm—OSP, which supports DiffServ, and a bandwidth reservation algorithm—RISP, which supports IntServ.

通过对ISP算法进行扩展，本文又提出了支持组播的EISP算法、支持区分服务／优先级调度的OSP算法和支持集成服务／带宽预约的RISP算法。

Active attack cryptanalysis based and fully scalable FGS encryption algorithm Aimed to the weakness of the current selective encryption algorithms in the sense of cryptanalysis, we design a active spacial—temporal correlation attack scheme and propose a both encryption strategies on base-layer and enhancement-layer. Not only the general FGS stream encryption is dealt with but also the case of FGST (fine granularity sealable temporal) is also well addressed.

2基于主动攻击安全的充分可扩展FGS加密算法针对目前压缩视频流加密算法所经常采用的选择加密方法，通过进行主动时域、空域相关性攻击，指出该类算法存在的问题，包括对于FGS基本层单独加密的安全分析，然后设计实现了基本层和增强层同时加密的安全策略，为保证FGS充分可扩展功能，算法同时还支持细粒度时域可扩展编码FGST(fine granularity scalable temporal)的情况。

In this paper, we also discuss the theory of the parallel simplex method. Undej the 2-dimensional space case, we present that simplex seriary have some properties, but we adopt some repairing measures. We proof the convergence of the parallel algorithm. At last, We give some numerical examples to indicate that the new idea is sometimes useful and helpful.

本文也对算法做了一些理论分析，主要在二维情形下，讨论了算法形成的单纯形序列本身所具有的性质，并对其做了相应的补救措施，对算法的收敛性给予了证明，最后做了一些数值实验，由于软硬件条件的限制，并行算法未能在并行计算机上实现，鉴于这种情况，我们所做的数值实验均是在串行机上完成的。

But we don't care about Battlegrounds.

但我们并不在乎沙场中的显露。

Ah! don't mention it, the butcher's shop is a horror.

啊！不用提了。提到肉，真是糟透了。