An Improved Immune Genetic Algorithm for Solving the Optimization Problems of Computer Communication Networks

1　IntroductionIndesigningacomputercommunicationnet work ,thenetworkaveragedelayisanimportantpa rameterinthenetworkperformance .Inthispaper,weonlyconsiderM /M/1networks,whichmeansthatthemessageprocessingtimeisaprobabilisticdensityfunctionwithnegativepower,thegroupar rivalandsendingisofPoissiondistributionwithasinglequeue .Supposethatthenetworktopologicalstructureandtheestimatesoftheexternaltrafficrequirementsaregiven ,howtoselecttheoptimalroutestobeusedbythecommunicatingnodesinthenetworksoast…     

遗传算法的改进及其在电力系统无功优化中的应用

针对无功优化的动态、多目标、多约束以及非线性特点,提出了基于简单遗传算法的改进算法,在简单遗传算法的基础上,添加了自适应控制和适应度排序思想,并对算法终止准则进行了改进。以IEEE14节点标准测试系统为例对该算法进行了有效性验证。仿真结果表明,该方法对电力系统的无功优化效果良好。     

频域吸收边界条件的构造理论

在频域中推导了适用于差分类数值方法的吸收边界条件的构造方法，并通过选取不同参数导出了几种现有的吸收边界条件。在计算了一般形式的吸收边界条件的反射系数之后，提出了一种简单实用的自适应吸收边界条件。     

Differential Evolution Algorithm Based Self-adaptive Control Strategy for Fed-batch Cultivation of Yeast

In the fed-batch cultivation of Saccharomyces cerevisiae, excessive glucose addition leads to increased ethanol accumulation, which will reduce the efficiency of glucose utilization and inhibit product synthesis. Insufficient glucose addition limits cell growth. To properly regulate glucose feed, a different evolution algorithm based on self-adaptive control strategy was proposed, consisting of three modules (PID, system identification and parameter optimization). Performance of the proposed and conventional PID controllers was validated and compared in simulated and experimental cultivations. In the simulation, cultivation with the self-adaptive control strategy had a more stable glucose feed rate and concentration, more stable ethanol concentration around the set-point (1.0 g•L^-1), and final biomass concentration of 34.5 g-DCW•L^-1, 29.2% higher than that with a conventional PID control strategy. In the experiment, the cultivation with the self-adaptive control strategy also had more stable glucose and ethanol concentrations, as well as a final biomass concentration that was 37.4% higher than that using the conventional strategy.     

Adaptive simulated annealing particle swarm optimization algorithm

Particle swarm optimization is widely used in various fields because of the few parameters to be set and the simple calculation structure.In order to improve the optimization speed and accuracy of the PSO,and to avoid falling into the local optimal solution,an adaptive simulated annealing PSO is proposed,which uses the hyperbolic tangent function to control the inertia weight factor for nonlinear adaptive changes,uses linear change strategies to control 2 learning factors,introduces the simulation annealing operation,set a temperature according to the initial state of the population,guide the population to accept the difference solution with a certain probability according to the Metropolis criterion,and ensure the ability to jump out of the local optimal solution.To verify the effect of the algorithm proposed in this paper,7 typical test functions and 5 algorithms proposed in the literature are selected for comparison and testing.According to the average value,standard deviation and number of iterations of the optimization results,the algorithm proposed in this paper has greatly improved the iteration accuracy,convergence speed and stability so as to overcome the shortcomings of particle swarm optimization.     

自适应演化软件研究进展*

自适应演化软件通过演化技术,为软件添加动态、柔性以及灵活可变的特征,使软件系统能更好地适应动态、开放以及难控的网络环境,并在普适计算、嵌入计算等领域表现出良好的应用前景,成为当前软件技术研究中备受关注的热点之一。为更好地研究自适应演化软件,需对现有研究成果进行总结和归纳。首先总结自适应演化的基本特征,指出其面临的挑战;在此基础上,从语言、体系结构和框架应用层面描述其研究成果,并对其进行分类与比较,进而给出相关概念结构;最后总结了其不足以及进一步的研究问题。     

空间光通信ATP系统粗跟踪平台的混合自适应控制

ATP系统的粗跟踪平台外框架对内框架的耦合作用以及内框架自身的不平衡所引起的加速度干扰是影响空间光通信系统光信号跟踪性能的重要因素。针对方位跟踪通道中的内框架系统结构,提出了应用一种混合自适应控制方法,该方法在设计自适应控制器时采用离散与连续相结合的方法,并将耦合作用和加速度干扰转换为对象的未建模动态进行处理。最终的仿真结果表明,被控对象在具有未建模动态和干扰的情况下,采用混合自适应控制算法能够获得较高的跟踪精度。     

显著性检测指导的高光区域修复

目的为解决传统的基于光照模型的高光修复算法无法很好地对高光区域存在饱和现象的单幅图像进行处理这一问题,提出一种显著性检测指导的高光区域修复算法。方法首先在亮度空间应用显著性模型,实现高光区域的自动检测和标记,之后运用改进的Exemplar-Based算法,综合利用图像的邻域和边缘信息,对标记的高光区域进行自适应修复,去除图像中的高光。结果分别对仿真及自然场景下的高光图像进行测试,实验结果表明,与原修复算法和传统高光去除算法相比,所提算法的修复效果更符合人眼视觉、修复后的图像质量更好。结论本文算法与Exemplar-Based算法及Tan方法相比,对高光区域存在饱和现象的单幅图像有较好的修复效果,并且有效地克服了传统高光去除算法受光照模型限制的缺点。     

面向移动机器人应用的跨平台自适应软件框架

摘要：自适应软件在移动机器人上具有广泛的应用前景,然而要在具有不同软硬件平台的移动机器人上开发自适应软件是一件非常困难的事情．．为了解决这个问题,提出并实现了一个面向移动机器人应用的跨平台自适应软件框架该框架屏蔽了运行平台的软硬件差异性,并使用规则文件将自适应逻辑分离出来,从而降低了自适应软件开发的难度。为了便于编写及检查规则文件,还实现了一个可视化的规则文件编辑器,用于自动生成模型图,并检查规则中存在的语法及逻辑错误i,最后,通过实验测试了框架的使用情况,并对框架的应用效果进行了评估、     

Adaptive particle swarm optimization method with stagnancy information

To improve the performance of the particle swarm optimization algorithm, the optimal network of the particle age structure with stagnation information is designed, and the information about this network is used to adaptively change the three key parameters of the particle swarm optimization algorithm. At the same time, an adaptive particle swarm optimization method with stagnancy information is proposed and specific optimization steps of this method are given. Four classical low and high dimension benchmark test functions are used to validate the performance of the optimization method, and a comparison study is made with gravitational search algorithm and the traditional particle swarm optimization algorithm without stagnancy information. The comparison study shows that the search efficiency of the proposed method is 2 times higher than that of other methods in the literature in the case of low dimensional multimodal functions. When the dimension of functions is higher than 2, the search efficiency of the proposed method is almost the same as that of other methods, but with the better ability to achieve global solution and local solutions, and the higher solving precision.