基于模型概率的多模型融合定轨建模及仿真

针对实际定轨系统中存在的不确定性和非线性性,提出了一种基于模型概率的多模型融合定轨方法.通过多个线性模型的组合来逼近卫星定轨复杂非线性时变过程,将卫星状态的最优估计与多模型融合方法相结合,利用残差的大小来设计性能指标函数,给出了两种模型概率的表示形式,并建立了多模型融合估计相应的算法.仿真结果表明,与单一模型定轨方法相比,该方法不仅能大大提高卫星定轨精度和可靠性,而且还可以最终辨识和估计模型参数的真值,且对外界环境发生的变化有很强的自适应能力.     

北京市用水结构与产业结构的成分数据回归分析

城市经济发展带来了产业结构和用水结构的明显变化,本文分析了用水结构受产业结构变化影响的变动规律.用水结构和产业结构是一系列按照时间顺序排列的成分数据,运用软件SIMCA-P 11.5建立了基于偏最小二乘回归的成分数据线性回归模型,证明了用水结构组分变动与产业结构变动有一致性.为城市水资源管理提供了合理有效的定量方法,并可作为对未来用水结构预测的基础.     

三维医学图像分割的改进量子进化搜索算法

传统量子进化算法用于搜索某些函数极值时精确度较低且稳定性较差.针对该问题,借鉴模拟退火算法,根据进化代数及个体的适应度值,修正了传统量子进化算法旋转门函数的旋转角度值,并应用于三维医学图像分割,从而形成了一种用于三维医学图像分割的改进量子进化算法.100次阈值计算实验结果表明,提出的分割算法与传统量子进化算法相比,在保持了传统量子进化算法收敛速度快特点的同时,可大大提高算法在三维分割中的精确性和稳定性.     

全球原油市场间信息溢出的实证研究——基于CCF方法与ECM模型

采用基于协相关函数(CCF)的Hong(2001)方法和基于协整理论的误差修正模型(ECM)系统研究了全球原油市场的Granger因果关系与信息溢出.研究市场包括伦敦、纽约、迪拜(Dubai)以及东南亚的塔皮斯(Tapis)和米纳斯(Minas)原油市场,结果显示伦敦和纽约的原油期货交易在信息溢出方面占主导地位,东南亚、迪拜、伦敦和纽约四个市场的原油现货交易处于弱势地位.采用Hong(2001)方法的研究结果表明,在10%水平上,纽约WTI期货是伦敦Brent期货下跌风险的Granger原因,因此WTI期货略占优势.此外,在检验Granger,因果关系和信息溢出方面,实证表明Hong(2001)方法优于ECM.     

基于OSG林地可视化系统设计与实现

森林、树木和花卉等植被实时可视化仿真是复杂虚拟园林环境中的重要组成部分.论文基于OpensceneGraph(OSG)和实时建模工具MuitiGen Creator(Creator)设计并实现了林分场景可视化系统.重点介绍了系统实现的框架和技术流程,并对如何在Creator中建立模型的层次结构关系进行了分析与研究.同时对该系统中使用的关键技术,如粒子系统、漫游设计和碰撞检测等实现方法进行了介绍.最后利用该方法对北京市八达岭地区林分场景进行了可视化模拟,模拟的场景逼真、自然,能满足用户实时交互的需要.     

基于压缩域信息的运动区域检测

运动对象检测是智能视频监控的基础,现有的运动对象检测算法在实时性和检测精度方面仍有待提高,提出了一种利用压缩域的信息运动区域检测算法,首先利用压缩过程中产生的运动矢量信息去除摄像机的背景运动,然后利用宏块的DCT系数,宏块类型等信息去除虚假的运动块,最后使用了形态学的腐蚀与扩张处理以提高检测精度.测试结果表明,本文算法速度快、能够准确检测出运动区域.     

基金持仓与商品期货价格关系的实证研究——以铜期货市场为例

为考察基金操作行为与铜期货价格之间的关系,利用美国商品期货交易委员会公布的交易商持仓报告提供的持仓信息,采用Granger因果检验方法分析了国际基金操作行为与国际铜期货价格之间的关系.结果表明,价格收益率正向Granger影响基金净多持仓,即收益率上升会引起基金净多持仓的增加.但一般而言,交易商包括基金的净持仓并不引领价格变化.另一方面,瞬时Granger因果检验的结果显示,基金净持仓与期货价格之间存在互相影响、互为因果的关系.     

Hybrid particle swarm optimization for multiobjective resource allocation

Resource allocation （RA） is the problem of allocating resources among various artifacts or business units to meet one or more expected goals, such a.s maximizing the profits, minimizing the costs, or achieving the best qualities. A complex multiobjective RA is addressed, and a multiobjective mathematical model is used to find solutions efficiently. Then, all improved particie swarm algorithm （mO_PSO） is proposed combined with a new particle diversity controller policies and dissipation operation. Meanwhile, a modified Pareto methods used in PSO to deal with multiobjectives optimization is presented. The effectiveness of the provided algorithm is validated by its application to some illustrative example dealing with multiobjective RA problems and with the comparative experiment with other algorithm.     

Optimal maintenance and replacement of extraction machinery

This paper considers a problem of optimal preventive maintenance and replacement schedule of equipment devoted to extracting resources from known deposits. Typical examples are oil drills, mine shovels, etc. At most one replacement of the existing machinery by a new one is allowed. The problem is formulated as an optimal control problem subject to the state constraint that the remaining deposit at any given time is nonnegative. We show that the optimal preventive maintenance, production rates, and the replacement and salvage times of the existing machinery and the new one, if required, can be obtained by solving sequentially a series of free-end-point optimal control problems. Moreover, an algorithm based on this result is developed and used to solve two illustrative examples.     

An improved branch-and-bound algorithm to minimize the weighted flowtime on identical parallel machines with family setup times

This article investigates identical parallel machines scheduling with family setup times. The objective function being the weighted sum of completion times, the problem is known to be strongly NP-hard. We propose a constructive heuristic algorithm and three complementary lower bounds. Two of these bounds proceed by elimination of setup times or by distributing each of them to jobs of the corresponding family, while the third one is based on a lagrangian relaxation. The bounds and the heuristic are incorporated into a branch-and-bound algorithm. Experimental results obtained outperform those of the methods presented in previous works, in term of size of solved problems.