基于序列二次规划法的分布式电源优化配置研究

针对分布式电源配置对配电网的影响,提出一种带二阶项配网潮流约束的方法解决分布式电源优化配置问题,以实现分布式电源价值的最大化。从降损角度出发建立优化配置的数学模型,并用序列二次规划求解优化问题。在充分发挥序列二次规划法收敛性好的基础上,提高计算精度,并适用于各种复杂的配电网络。以IEEE33节点系统为例,验证所提方法在分布式电源优化配置问题求解中具有很强的全局搜索能力,可以有效、准确地实现分布式电源的最优配置,计算过程简单可靠,具有实用价值。     

Zames-Falb Multipliers for Quadratic Programming

In constrained linear model predictive control, a quadratic program must be solved on-line at each control step, and this constitutes a nonlinearity. If zero is a feasible point for this quadratic program then the resultant nonlinearity is sector bounded. We show that if the nonlinearity is static then it is also monotone and slope restricted; hence, we show the existence of Zames-Falb multipliers for such a nonlinearity. The multipliers may be used in a general and versatile analysis of the robust stability of input constrained model predictive control.     

Local Classifier Weighting by Quadratic Programming

It has been widely accepted that the classification accuracy can be improved by combining outputs of multiple classifiers. However, how to combine multiple classifiers with various (potentially conflicting) decisions is still an open problem. A rich collection of classifier combination procedures-many of which are heuristic in nature-have been developed for this goal. In this brief, we describe a dynamic approach to combine classifiers that have expertise in different regions of the input space. To this end, we use local classifier accuracy estimates to weight classifier outputs. Specifically, we estimate local recognition accuracies of classifiers near a query sample by utilizing its nearest neighbors, and then use these estimates to find the best weights of classifiers to label the query. The problem is formulated as a convex quadratic optimization problem, which returns optimal nonnegative classifier weights with respect to the chosen objective function, and the weights ensure that locally most accurate classifiers are weighted more heavily for labeling the query sample. Experimental results on several data sets indicate that the proposed weighting scheme outperforms other popular classifier combination schemes, particularly on problems with complex decision boundaries. Hence, the results indicate that local classification-accuracy-based combination techniques are well suited for decision making when the classifiers are trained by focusing on different regions of the input space.     

一种基于FPGA的二次规划求解方法

二次规划是一类重要的优化问题,许多工程上的优化问题都可以归结为二次规划的求解,如：预测控制,最小二乘等。嵌入式技术的发展使得嵌入式系统广泛地应用于人类生活的方方面面。由于二次规划的求解需要大量的计算,因此在传统基于ARM的嵌入式平台上实现比较困难。FPGA并行计算,硬件加速的特点使得在嵌入式平台上快速求解二次规划成为可能。本文主要介绍了一种基于FPGA的二次规划求解算法,首先介绍了二次规划的求解算法,然后将浮点算法改为定点算法,再采用Impulse C将定点算法变为HDL语言,最后通过实例验证了此方法的正确性。     

Designing Camera Networks by Convex Quadratic Programming

In this paper, we study the problem of automatic camera placement for computer graphics and computer vision applications. We extend the problem formulations of previous work by proposing a novel way to incorporate visibility constraints and camera‐to‐camera relationships. For example, the placement solution can be encouraged to have cameras that image the same important locations from different viewing directions, which can enable reconstruction and surveillance tasks to perform better. We show that the general camera placement problem can be formulated mathematically as a convex binary quadratic program (BQP) under linear constraints. Moreover, we propose an optimization strategy with a favorable trade‐off between speed and solution quality. Our solution is almost as fast as a greedy treatment of the problem, but the quality is significantly higher, so much so that it is comparable to exact solutions that take orders of magnitude more computation time. Because it is computationally attractive, our method also allows users to explore the space of solutions for variations in input parameters. To evaluate its effectiveness, we show a range of 3D results on real‐world floorplans (garage, hotel, mall, and airport).     

一种基于非线性规划的多项式PLS算法

在基于误差的多项式偏最小二乘(PLS)的基础上,提出了一种基于带约束的非线性规划的多项式PLS算法,利用罚函数法计算最优的输入权值和内部关系式的参数.对催化裂化主分馏塔侧线柴油95%点的软测量应用结果表明,该算法和基于误差的多项式PLS相比,模型拟合精度高而且计算量较小,能获得较高的累计方差贡献率,并具有良好的预报能力.     

一种基于非线性规划的多项式PLS算法

在基于误差的多项式偏最小二乘(PLS)的基础上,提出了一种基于带约束的非线性规划的多项式PLS算法,利用罚函数法计算最优的输入权值和内部关系式的参数。对催化裂化主分馏塔侧线柴油95%点的软测量应用结果表明,该算法和基于误差的多项式PLS相比,模型拟合精度高而且计算量较小,能获得较高的累计方差贡献率,并具有良好的预报能力。     

大规模结构化二次规划并行算法

在内点算法(IPM)框架基础上,分析具有分块带边结构系数矩阵与箭形结构二次项的二次规划(QP)问题,导出其既约与最简既约修正方程.对既约修正方程系数矩阵进行置换,使其具有箭形分块结构,并结合该结构与解耦技术给出修正方程的并行求解算法,设计QP问题的并行IPM结构.在集群环境下的数值实验结果表明,该算法具有较好的加速比和...     

基于微粒群优化的序贯二次规划方法

文章针对约束非线性优化问题,将微粒群优化算法(PSO)和序贯二次规划(SQP)算法结合起来,提出了一种解决此类问题的有效算法。PSO可以看作是全局搜索器,而SQP则主要执行局部搜索。对于那些具有多个局部极值点的优化问题,大大增加了获得全局极值点的几率。由于PSO具有快速全局收敛的特点,同时SQP的局部搜索能力很强,所以所提算法可以快速获得全局最优值。将基于PSO的序贯二次规划算法在两个标准优化问题上进行仿真,结果证明与标准的PSO和SQP相比,算法具有明显的优越性。     

一类特殊凸二次双层规划的算法

根据值型凸二次双层规划的Johri对偶理论,讨论一类特殊双层规划——上层仅含一个不等式约束的非减值型线性．凸二次双层规划的办法,通过把对其Johri对偶规划的求解转化为对有限个凸二次规划的求解,给出求解该类双层规划的一种多项式时间算法。     

分布式并行约束归纳逻辑程序设计研究

CILP是关系数据挖掘的主要技术之一。为提高CILP系统的效率,提出了一种基于C3模型,元学习技术和主从式静态负载平衡策略的分布式并行CILP算法,并实现了一个基于COW机群结构的分布式并行CILP原型系统。实验表明该算法是高效的,能获得较好的负载平衡,较高的加速比和并行效率。     

适用于分布式程序设计的图示化模型

VMDP(visual mode for distributed programming)模型是一个基于图标的面向分布式程序设计的图示化模型.它用图标表示分布式系统中的对象及其控制,例如,用车辆、路口和红绿灯等图标分别表示进程、资源和进程控制,从而使分布式系统中进程之间的同步、异步、互斥、共享等协调关系变得十分直观和易于理解.VMDP模型可以广泛应用到分布式系统模型、网络程序设计、并行程序设计和分布式程序设计等领域.     

一种面向分布式系统的程序设计模式

分布式系统的程序设计模式主要包括多线程模式和事件驱动模式,其中事件驱动模式占据了主导地位。本文讨论了这两种模式的不足,以及Coroutine模式相对它们的优点,并认为Coroutine模式是最适合分布式系统的程序设计模式。本文在此基础上提出了Libresync,它是一个基于Coroutine模式的分布式系统基础支持库。它既能给应用开发带来非常清晰的控制流程,又具有很高的灵活性和表达力,性能也能满足大多数需求。     

分布式并行程序设计范例

本文介绍了几种分布式并行程序设计范例：计算－汇集－广播，分而治之，流水线，处理机场等。人们可参考上述范例，进行并行程序设计。     

Distributed Parallel Computing Using Navigational Programming

Message Passing (MP) and Distributed Shared Memory (DSM) are the two most common approaches to distributed parallel computing. MP is difficult to use, whereas DSM is not scalable. Performance scalability and ease of programming can be achieved at the same time by using navigational programming (NavP). This approach combines the advantages of MP and DSM, and it balances convenience and flexibility. Similar to MP, NavP suggests to its programmers the principle of pivot-computes and hence is efficient and scalable. Like DSM, NavP supports incremental parallelization and shared variable programming and is therefore easy to use. The implementation and performance analysis of real-world algorithms, namely parallel Jacobi iteration and parallel Cholesky factorization, presented in this paper supports the claim that the NavP approach is better suited for general-purpose parallel distributed programming than either MP or DSM.     

CSM: A Distributed Programming Language

This paper presents an overview of a distributed programming language called Communicating Sequential Modules or CSM, intended to support distributed computing. Developed from Modula-2 and CSP, CSM has been implemented on the ZCZ distributed microcomputer system consisting of several LSI-11 microcomputers. Its implementation is also described.     

基于API的实时分布对象编程方法

文中主要讨论基于C＋＋和Java类库结构的应用程序接口（API）,用于支持高水平,高精度分布实时对象的编程方法,该方法不需要新的语言解释器。此外,还详细讨论了实时对象编程的基本特点和各类API的实现细节。