Dual–primal proximal point algorithms for extended convex programming

This paper presents a class of dual–primal proximal point algorithms (PPAs) for extended convex programming with linear constraints. By choosing appropriate proximal regularization matrices, the application of the general PPA to the equivalent variational inequality of the extended convex programming with linear constraints can result in easy proximal subproblems. In theory, the sequence generated by the general PPA may fail to converge since the proximal regularization matrix is asymmetric sometimes. So we construct descent directions derived from the solution obtained by the general PPA. Different step lengths and descent directions are chosen with the negligible additional computational load. The global convergence of the new algorithms is proved easily based on the fact that the sequences generated are Fejér monotone. Furthermore, we provide a simple proof for the O(1/t) convergence rate of these algorithms.     

Data-based multiple-model prediction of the production rate for hematite ore beneficiation process

The prediction of the production rate of the hematite ore beneficiation process is important to plant-wide optimization. This paper presents a data-based multi-model approach to predict the production rate with multiple operating modes. The inputs of the predictive model are the performance indices of each unit process, and the output is the global production index (the production rate) of the hematite ore beneficiation process. The multiple models are developed by integrating the fuzzy clustering algorithm and machine learning algorithm. A global model, Takagi–Sugeno–Kang fuzzy model, and multiple neural network model were compared using the data obtained from a practical industrial process, and the effectiveness of the proposed algorithm was proven.     

异构Hadoop集群下的比例数据分配策略

针对异构Hadoop环境下仍采用均等的数据分配方法将严重降低MapReduce的性能,提出比例数据分配策略。通过计算异构集群中各节点的计算比率,将已经分割好的数据块重新进行组合,形成数个按比例划分的数据块。每个节点根据自身性能来选择所分配和存储的数据块,从而使异构Hadoop集群中各节点处理数据的时间大致相同,降低节点之间数据的移动量。实验验证了提出的比例数据分配方法可以有效地提高MapReduce的性能,并使数据负载均衡。     

深度信念网络在故障指示器检测中的应用

电子产品在生产过程中需进行产品检测,以故障指示器的检测为例,结合深度信念网络(DBN)技术实现了自动检测.深度信念网络由于其具有无监督预训练的优势,将其应用于实际系统,对现场的故障指示器视频图像的动作状态进行了分类实验.实验结果表明:深度信念网络分类算法相比于支持向量机(SVM)分类算法和BP分类算法有明显的优势,正确识别率达到了100％.该算法在产品检验的应用中满足生产测试的要求,且降低了人工测试的劳动强度,缓解了视觉疲劳问题.     

基于次锚节点的无线传感器网络改进加权质心定位算法

针对加权质心定位算法（ WCLA）对锚节点数量要求较高和定位精度较低的缺陷,提出一种基于次锚节点的改进加权质心定位算法（ IWCLA-SAN）。该算法在加权因子中引入修正系数,以提高定位精度;同时,将基于粒子群优化（ PSO）的定位算法的未知节点升级为次锚节点,在锚节点数量有限的情况下,以提高定位精度和定位覆盖率。仿真结果表明：该算法能有效提高定位精度和定位覆盖率。     

城市区域交通信号迭代学习控制策略

城市交通流具有复杂的非线性动态特性, 在交通控制中难以对其进行精确的数学建模; 同时, 以天为周期, 宏观交通流又呈现出明显的周期性特征. 鉴于此, 提出一种基于迭代学习的城市区域交通信号控制策略, 通过对交通信号的迭代控制, 使路段的平均占有率收敛于期望占有率, 从而使绿灯时间得到充分利用并防止交通拥堵的发生, 保证了交通流在路网中的高效平稳运行. 严格的理论推导证明了该方法的收敛性, 仿真结果验证了该方法的有效性.

     

基于NSGA2与FIuent耦合的分析方法翼型优化

将分析方法引入飞行器气动优化设计,在FIuent软件中进行二次开发,编写了计算熵产率的UDF,来阐述分析方法在气动优化中的作用。以二维翼型为例,通过NURBS曲线进行翼型参数化建模,将NSGA2优化算法与CFD计算耦合起来,计算低雷诺数、5°攻角下的翼型升阻比和熵产率,得到最大升阻比和最小熵产率不断调和的翼型的Pareto解。结果显示,与基准翼型相比,在升阻比提高的条件下,流场熵产率减少,能量效率提高。而且优化翼型的熵产率随着升阻比的增加而增大。     

基于曲率匹配和递归排序的自适应排样算法

为提高盘状毛坯的使用率,提出一种口腔修复加工中模型边界在盘状毛坯中的排样算法,主要包括边界匹配、多边形定位及递归排序.首先基于协方差矩阵及矩阵SVD分解算法对模型多边形进行分段,并采用等弧长曲线采样曲率匹配确定待匹配模型边界;然后依毛坯边界角度分布及沿圆周排样的思想确定模型轮廓的旋转和平移定位;最后提出一种基于包络率的递归排序算法,对在排样过程中发现的大孔洞可动态地调整排样顺序.实验结果表明,该算法可以处理不规则模型边界在任意形状毛坯中的排样,能有效地降低加工成本.     

Gain‐scheduled filtering for linear parameter‐varying systems using inexact scheduling parameters with bounded variation rates

This paper is concerned with the problem of full‐order H₂ linear parameter‐varying filter design for continuous‐time systems with bounded rate of variations under the condition that the scheduling parameters do not exactly fit the real ones. The scheduling parameters and their derivatives are supposed to belong to polytopes with known vertices. The synthesis conditions are formulated in terms of parameter‐dependent bilinear matrix inequalities by means of parameter‐dependent Lyapunov function and introducing some extra variables for the filter design. An iterative procedure is presented to cast the bilinear matrix inequalities problem into a linear matrix inequality optimization problem. The design of robust filters for both time‐varying and time‐invariant systems can be viewed as particular cases of the proposed method. The merit of the method presented in this paper lies in two fields. The first pertains to dealing with the measurement uncertainty in a less conservative manner than available approaches in the gain‐scheduled filtering problem. The second is to provide more efficient methods than the existing ones in the literature for the robust filter design. Copyright © 2015 John Wiley & Sons, Ltd.     

MCS-51系列单片机串行通信波特率的研究

阐述了89C51单片机串行通信口的结构及波特率的计算方法,通过对89C52串行通信口波特率发生器结构的分析,指出了89C52产生波特率的两种方式。计算出了89C51和89C52产生波特率与初值的对应关系,找出了波特率的最大值,给出了初始化编程的实例。