SVSSI (X)控制图的经济设计

研究了SVSSI控制图的经济性能,运用受控和失控两种状态构建了马尔可夫链状态空间,给出了费用函数.通过数值实例,以AATS和ECTU为准则,比较了控制图对过程波动的检测性能.结果表明SVSSI控制图的经济性能要优于VSI和VSSI控制图.进一步,应用遗传算法搜索了SVSSI控制图经济设计的最优解.     

拉丁超立方体抽样遗传算法求解图的二划分问题

图的二划分问题是一个典型的NP-hard组合优化问题, 在许多领域都有重要应用. 近年来, 传统遗传算法等各种智能优化方法被引入到该问题的求解中来, 但效果不理想. 基于理想浓度模型的机理分析, 利用拉丁超立方体抽样的理论和方法, 对遗传算法中的交叉操作进行了重新设计, 并在分析图二划分问题特点的基础上, 结合局部搜索策略, 给出了一个解决图二划分问题的新的遗传算法, 称之为拉丁超立方体抽样遗传算法. 通过将该算法与简单遗传算法和佳点集遗传算法进行求解图二划分问题的仿真模拟比较, 可以看出新的算法提高了求解的质量、速度和精度.     

均匀设计抽样混合遗传算法求解图的二划分问题

遗传算法(GA)的运行机理及特点是具有定向制导的随机搜索技术,其定向制导的原则是:导向以高适应度模式为祖先的\"家族\"方向。以此结论为基础,利用均匀设计抽样(UDS)的理论和方法,对遗传算法中的交叉操作进行重新设计,并在分析图二划分问题特点的基础上,结合局部搜索策略,给出了一个求解图二划分问题的新遗传算法,称之为基于均匀设计抽样的混合遗传算法。最后将该算法与简单遗传算法和佳点集遗传算法进行比较。通过模拟比较,可以看出新算法不但提高了算法的求解速度和精度,而且避免了常有的早期收敛现象。     

基于双柔化系数在线调整的广义预测控制

在预测控制系统中,其控制品质与控制器的参数整定有很大的关系,特别是性能指标中的输出柔化系数及输入柔化系数。针对广义预测控制算法中控制参数整定困难这一缺点,利用BP神经网络,提出一种基于双柔化系数设计的广义预测控制算法,实现了广义预测控制中输入输出柔化系数的在线调整。仿真结果表明,该算法无论在跟踪性能、控制精度及鲁棒性上,均优于固定参数的广义预测控制算法,并对干扰有一定的抑制作用。     

The variable sampling interval run sum X‾ control chart

Traditional control charts for process monitoring are based on taking samples from the process at fixed length sampling intervals. More recently, research works focused on the use of variable sampling intervals (VSIs), where the lengths of the sampling intervals are varied according to the process quality. A short sampling interval is considered when the process quality indicates a possible out-of-control situation while a long sampling interval is considered, otherwise. In this paper, the VSI run sum (RS) chart is proposed with its optimal scores and parameters determined using an optimization technique to minimize the out-of-control average time to signal (ATS) or the adjusted average time to signal (AATS). A Markov-chain method is used to evaluate both the ATS and AATS of the proposed chart, for the zero and steady state cases, respectively. Results show that the VSI RS chart is considerably more efficient than the basic RS chart. The VSI RS chart performs generally well compared with other competing charts, such as the standard , synthetic , exponentially weighted moving average (EWMA) , VSI and VSI EWMA charts. The sensitivity of the VSI RS chart can be enhanced further by adding more scoring regions or a head-start feature. An illustrative example is presented to explain the implementation of the proposed VSI RS chart.     

基于多重相关状态采样的多元EWMA控制图

为提高控制图的监测效率,提出了一种基于多重相关状态采样的多元EWMA控制图,并利用改进后的马尔可夫链方法计算控制图的平均运行长度。根据不同参数下控制图的平均运行长度,分析了控制图在失控和受控状态下的性能表现,并与其它多元EWMA控制图进行比较。模拟结果表明,该控制图具有良好的监测能力。最后用一组模拟数据来说明该方法的使用。     

关联交叉口子区的信号优化控制方法

在交叉口群的信号优化控制过程中,针对遗传算法早熟收敛且对相邻交叉口关联性考虑较少的问题,提出一种关联交叉口子区的信号优化控制方法.利用软集合理论将关联性强的交叉口划分在同一个子区;采用基于共享函数的小生境技术调整群体中个体的适应度并自适应地调整算法的交叉概率Pc和变异概率Pm对遗传算法进行改进;使用改进的遗传算法对关联...     

遗传算法的平均收敛速度及其估计

给出了独立于表示的变异算子和交叉算子的数学描述, 建立了遗传算法种群的精确马尔可夫链模型, 导出了种群中最佳个体的马尔可夫链及其随机矩阵, 将遗传算法的平均收敛速度定义为最佳个体转移至吸收态的平均吸收时间的数学期望, 提出了应用最佳个体的随机矩阵估计遗传算法平均收敛速度的理论方法和计算步骤.     

基于改进遗传算法的分形图像编码

为解决传统分形图像编码方案中块匹配时间过长的问题,提出一种结合图像块平均偏差的改进遗传算法,利用改进遗传算法的最优解搜索能力替代分形图像编码中复杂的块匹配过程,结合对比度因子的约束,限定遗传算法的搜索空间,缩短编码时间。实验结果表明,该方法与结合遗传算法的同类改进算法相比,能在缩短编码时间的同时,有效提高解压图像质量。     

基于改进遗传算法的分形图像编码

为解决传统分形图像编码方案中块匹配时间过长的问题,提出一种结合图像块平均偏差的改进遗传算法,利用改进遗传算法的最优解搜索能力替代分形图像编码中复杂的块匹配过程,结合对比度因子的约束,限定遗传算法的搜索空间,缩短编码时间。实验结果表明,该方法与结合遗传算法的同类改进算法相比,能在缩短编码时间的同时,有效提高解压图像质量。     

基于时序推断的拥塞控制策略的性能分析

通过对TD、RED等算法进行较精确的Markov建模,以理论分析和数值模拟的方法对各种拥塞控制策略的性能进行深入的研究和比较,并着重从时间序列的角度分析平均队列长度计算方法的数学过程和理论依据,进而提出基于时序预测推断的平均队列长度的计算方法,给出相应的数学模型和数值模拟性能曲线,结果证明:新的算法在系统稳定性和资源利用率上表现出明显的优越性,其走势更加接近理想的性能曲线.最后考察了各算法结合优先级丢弃策略的性能表现.     

Economic design of two-stage non-central chi-square charts for dependent variables

Non-central chi-square charts are more effective than the joint and R charts in detecting small mean shifts or variance changes of a performance variable. However, the cost may be high to monitor a primary quality characteristic, such as the weight of each bag in a cement filling process. It is more economical to monitor a surrogate variable, for example, the milliampere of the load cell. When the correlation of the performance variable of surrogate variable exists, this article proposes a two-stage charting design to monitor either the performance variable or its surrogate variable in an alternating fashion rather than monitoring the performance variable alone. The proposed method simplifies process monitoring when users only concern about whether a process is in control or not. The application of the proposed method and the advantages of the proposed chart over the existing methods are presented through an example. Numerical results show that the proposed chart is insensitive on the correlation of the performance variable and surrogate variable even when the historical information on the correlation coefficient is not very accurate.     

A variable parameter Shewhart control scheme for joint monitoring of process mean and variance

This paper presents a new Statistical Process Control model for the economic optimization of a variable-parameter control chart monitoring a process operation where two assignable causes may occur, one affecting the mean and the other the variance of the process. Therefore, it is possible for the process to operate in statistical control, when none of the two assignable causes has occurred, or under the effect of one or both the assignable causes. By making the assumption that the occurrence rate of each assignable cause is exponential, a Markov chain approach is utilized to determine the probabilities that the process operates at any of the above possible states. The model uses an economic (or an economic/statistical) optimization criterion for the time to the next sampling instance, the size of the next sample, as well as the control limits of the inspection. That is, all design parameters of the control scheme are selected so as to minimize the total expected quality-related costs. The superiority of the proposed model is estimated by comparing its expected quality control cost vs. the outcome of the Fp (Fixed-parameter) Shewhart control chart, the Variable Sample Size (VSS) control chart, the Variable Sampling Interval (VSI) and the Variable Sample Size and Sampling Interval (VSSI) control chart, for a benchmark of examples. The numerical investigation indicates that the economic improvement of the proposed model may be significant.