Generalizing the CHOKe flow protection

This paper proposes a simple and stateless active queue management (AQM) scheme, called geometric CHOKe (gCHOKe), to protect responsive flows from unresponsive ones. gCHOKe has its root in and is a generalization of the original CHOKe. It provides an additional power of protection, achieved by introducing an extra flow matching trial following each successful flow comparison of packets. The maximum number of comparisons permitted for an arrival can be controlled by a parameter called maxcomp. The quality of flow protection improves with maxcomp. Compared to the plain CHOKe (which is just the simplest case of gCHOKe), our analysis and simulations show that the scheme can achieve over 20% improvement in the bounds of both bandwidth and buffer space used by an aggressive flow. In addition, up to 14% of the total link capacity can be saved from the unresponsive flow, allowing responsive or rate-adaptive flows to obtain a better share of resources in the router.     

Chemical reaction optimization with greedy strategy for the 0–1 knapsack problem

The 0–1 knapsack problem (KP01) is a well-known combinatorial optimization problem. It is an NP-hard problem which plays important roles in computing theory and in many real life applications. Chemical reaction optimization (CRO) is a new optimization framework, inspired by the nature of chemical reactions. CRO has demonstrated excellent performance in solving many engineering problems such as the quadratic assignment problem, neural network training, multimodal continuous problems, etc. This paper proposes a new chemical reaction optimization with greedy strategy algorithm (CROG) to solve KP01. The paper also explains the operator design and parameter turning methods for CROG. A new repair function integrating a greedy strategy and random selection is used to repair the infeasible solutions. The experimental results have proven the superior performance of CROG compared to genetic algorithm (GA), ant colony optimization (ACO) and quantum-inspired evolutionary algorithm (QEA).     

CMMB系统同步算法FPGA实现及验证

为了提高CMMB系统广播信号接收同步精度,提出了一种使用CMMB信标进行载波和定时精确同步的算法。首先通过基于循环前缀的算法进行小数倍频偏估计和定时粗同步,再利用同步信号中伪随机序列的相关特性进行整数倍频偏估计和精确定时同步。仿真表明,在高斯白噪声下,CMMB系统同步算法的小数倍频偏性能与基于循环前缀的算法相当,但可以进行整数倍估计且定时精度高,在多径信道下,CMMB系统同步算法的估计精度优于基于循环前缀算法。实验结果验证了仿真的正确性。     

超差特征量指标集约束下PID调节器的满意优化

针对一类具有目的域的控制系统,提出将一组由滞留时间、超差时间以及随机穿越周期时间等构成的超差特征量指标纳入满意PID调节器的目标函数集中进行研究。将PID调节器的参数设计转化为局部状态反馈问题,推导出带状目的域下超差特征量指标的解析表达式,并分析了其与稳定裕度、动态误差系数以及稳态输出方差指标之间的相容性;当上述指标相容时,给出了一种利用双群体机制下的差分进化算法和内点法相结合对PID调节器参数进行优化求解的策略;数值算例表明了所提方法的有效性。     

关于电力系统中对智能控制技术的应用分析研究

在电力系统中加入人工智能控制技术的应用,能够有效解决非线性问题.本文描述了模糊技术、神经网络、专家系统这三种智能控制技术的特点,并就其在电力系统中的应用现状进行分析,阐述了智能控制对于电力系统无功电压控制、切负荷、继电保护等方面的作用.     

基于模糊灰度共生矩阵与隐马尔可夫模型的断口图像识别

纹理通常由空间分布和灰度分布共同描述,灰度共生矩阵(GLCM)能兼顾二者,故广泛应用于纹理分析中。在计算GLCM时,为降低其维数,需对纹理图像进行灰度量化,这必然丢失部分图像信息。灰度量化时,由灰度值与量化区间中心值的不同距离,构造出相应的模糊隶属度函数,并定义了模糊灰度共生矩阵(FGLCM)。通过对断口图像FGLCM的14个特征统计量进行相关性分析,选择角二阶矩和熵等7个统计量作为特征参数,并验证了其有效性。最后,在4类典型断口图像的特征空间上,采用隐马尔可夫模型(HMM)进行分类识别。实践表明,FGLCM比已有的GLCM能更好地表征断口特性,且在HMM状态数为3时,断口分类的平均识别率可达98%。     

基于SURF特征的高动态范围图像配准算法

同一场景的多曝光图像序列被广泛的应用于高动态范围图像（HighDynamicRangeImage）的合成中。但是,在多曝光图像序列的采集过程中,相机抖动、场景运动等因素会对合成图像的质量产生较大的影响。此外,离镜头较近的大目标往往由于显著的三维形状,在序列图中产生较大的视差效应,也会对合成图像产生消极影响。该文提出一种基于SURF特征点的三维图像配准算法,实验证明该算法在近距离大目标情形下较之传统配准算法MTB（MeanThresholdBitmap,均值二值化）可以获得更好效果。     

VB编程中使用数据库调用图片的方法研究

在管理系统中,除了保存大量的文字信息以外,有时候也需要保存一定数量的图片。因此,在VB编程中使用数据库对图片进行编辑是很重要的事情,本文以Access数据库为例,讨论解决这个问题的一些方法。     

测距传感器数据在线自适应加权融合

针对移动机器人的测距系统,采用了红外线传感器与超声波传感器共同测距,避免了因使用单个传感器进行多次测量而降低系统的实时性和产生信号串扰问题;应用自适应加权数据融合估计算法对实时测量数据进行在线融合估计,只对当前采样时刻的测量数据进行自适应加权融合,而各传感器的加权因子则通过传感器的测量数据进行方差在线学习估计以自适应方式进行调整,使融合结果的均方误差始终最小,实现两种传感器在功能上的互补;实验结果表明,该方法提高了整体测距精度,得到了被测距离更加准确的估计.     

A strategic classification support system for brownfield redevelopment

Brownfield redevelopment (BR) is an ongoing issue for governments, communities, and consultants around the world. It is also an increasingly popular research topic in several academic fields. Strategic decision support that is now available for BR is surveyed and assessed. Then a dominance-based rough-set approach is developed and used to classify cities facing BR issues according to the level of two characteristics, BR effectiveness and BR future needs. The data for the classification are based on the widely available results of a survey of US cities. The unique features of the method are its reduced requirement for preference information, its ability to handle missing information effectively, and the easily understood linguistic decision rules that it generates, based on a training classification provided by experts. The resulting classification should be a valuable aid to cities and governments as they plan their BR projects and budgets.