一个面向OLAP应用的多维数据查询语言及其在对象关系数据库中的实现

该文提出了一个面向联机分析处理(OLAP)的多维查询语言,为多维查询的方便表达提供了一个直观的高层界面。这一查询语言的独特之处在于能够很好地支持具有继承关系的维层次结构,这种维层次结构在传统的关系型的ROLAP中是难于用星型/雪花模式表示的。文章将这一查询语言实现于对象关系数据库之上。并通过实例进行说明,对象关系数据库所特有的基本类型扩展能力、复杂对象的表示以及继承机制,使得对多维数据的描述更加灵活、多维操作更为高效。     

分析服务组件模型在数据挖掘中的研究与应用

分析服务组件是SQLServer2000中专门用于进行数据挖掘的工具组件,它基于可视化的Windows开发平台。文中讨论了用分析服务组件进行数据挖掘的方法,介绍了用类似SQL的DDL构建了数据挖掘应用的一个实例。     

Recursive identification for multidimensional ARMA processes with increasing variances

~~Recursive identification for multidimensional ARMA processes with increasing variances1. Anderson, T. W., The statistical Analysis of Time Series, New York: Wiley, 1971. 2. Brockwell, P. T., Davis, R. A., Time Series: Theory and Methods, New York: Springer, 1987. 3. Caines, P. E., Linear Stochastic Systems, New York: Wiley, 1988. 4. Hanann, E. J., Diestler, M., The Statistical Theory of Linear Systems, New York: Wiley, 1988. 5. Ljung, L., Soderstrom, T. S., T…     

一种基于维层次聚集树的Cube增量更新算法

提出利用Cube中的维层次聚集树（dimension hierarchy aggregate tree,简称DHA-Tree）来对聚集Cube进行增量更新维护,在维层次聚集Cube中进行数据插入和删除等数据更新时,充分利用维层次聚集树中的维层次前缀,由下向上用更新前后的差值对受到更新结点影响的所有祖先结点进行增量更新.在插入新维数据时,在不需要重新构建聚集Cube就可以对聚集Cube进行增量更新,从而减少了Cube的更新时间.对基于维层次聚集树的聚集Cube与传统Cube进行了算法性能分析和比较,结果表明本文所提出的聚集Cube的增量更新算法性能最佳.     

VisualDM：一个灵活的可视化数据挖掘系统

如果要建造一个健壮的数据挖掘系统，仅仅依靠挖掘算法是不够的。目前的挖掘算法还没有完全“智能”化，所以挖掘有用的信息常常不是很有效。不过可视化技术给了我们很大的帮助，我们将挖掘算法和可视化技术结合起来，从而实现了数据挖掘系统VisualDM。     

Image Manifolds which are Isometric to Euclidean Space

Recently, the Isomap procedure [10] was proposed as a new way to recover a low-dimensional parametrization of data lying on a low-dimensional submanifold in high-dimensional space. The method assumes that the submanifold, viewed as a Riemannian submanifold of the ambient high-dimensional space, is isometric to a convex subset of Euclidean space. This naturally raises the question: what datasets can reasonably be modeled by this condition? In this paper, we consider a special kind of image data: families of images generated by articulation of one or several objects in a scene—for example, images of a black disk on a white background with center placed at a range of locations. The collection of all images in such an articulation family, as the parameters of the articulation vary, makes up an articulation manifold, a submanifold of L ². We study the properties of such articulation manifolds, in particular, their lack of differentiability when the images have edges. Under these conditions, we show that there exists a natural renormalization of geodesic distance which yields a well-defined metric. We exhibit a list of articulation models where the corresponding manifold equipped with this new metric is indeed isometric to a convex subset of Euclidean space. Examples include translations of a symmetric object, rotations of a closed set, articulations of a horizon, and expressions of a cartoon face. The theoretical predictions from our study are borne out by empirical experiments with published Isomap code. We also note that in the case where several components of the image articulate independently, isometry may fail; for example, with several disks in an image avoiding contact, the underlying Riemannian manifold is locally isometric to an open, connected, but not convex subset of Euclidean space. Such a situation matches the assumptions of our recently-proposed Hessian Eigenmaps procedure, but not the original Isomap procedure.     

多维组合预测的贝叶斯极大似然估计

为了实际预测的需要,提出了多维组合预测问题,即若干单项多维预测的变权组合预测.在各单项预测无偏且服从正态分布前题下,求出了p时刻预测向量Xp的先验分布密度和后验分布密度.利用主观先验信息、预测信息和样本信息,运用贝叶斯估计方法,得到了Xp的贝叶斯极大似然估计,其权重随时刻p的改变而改变.本方法充分利用了多维变量间的相关信息,进一步提高了预测的科学性和有效性,体现了对样本信息和预测信息的进一步综合应用.     

Optimizing Spray and Combustion in Diesel Engine by Multidimensional Numerical Simulation

The calculation of spray and combustion in diesel engines is described by using the softwares FIRE and BOOST. The application of the resulting computational method to the simulation of fuel spray and breakup, mixture formation and combustion in a heavy duty diesel is presented. According to detailed insight into the governing processes provided by the simulation results, various aspects of the dependence of the spray propagation and combustion on the chamber geometry and spray angle are discussed. Then, global cylinderaveraged pressure traces are extracted from the space and time resolved field quantities and compared to incylinder pressure measurements. Finally, an optimized configuration of the chamber geometry and spray angle with a new injection rate of higher injection pressure is proposed.     

基于地震灾害场景的主动配电网多维韧性评估方法

为了分析主动配电网承受破坏性扰动事件以及快速恢复重要负荷的韧性支撑能力,融合相量测量单元（PMU）高精度动态感知能力提出了一种新的以地震灾害场景为背景的主动配电网多维韧性评估方法。阐述了配电网韧性的基本概念及特征,并将地震作为极端事件代表,构建了反映配电线路故障率与地震动峰值加速度加权均值的模型,继而采用非序贯蒙特卡罗抽样和K-means++聚类算法筛选出代表性的地震场景;基于系统配置的PMU的强感知力建立反映韧性电网应变力、防御力、恢复力和协同力的评估指标,形成韧性多维特征空间,进而利用事件集点簇中心与最优韧性点的加权欧氏距离评估系统多维综合韧性;分析增强电力线路强度、提高联合系统中分布式电源可供容量这2种措施对系统韧性提升的影响,挖掘韧性电网对抗震防灾的学习力。最后,通过改进的PG&E69系统验证所提方法的有效性和准确性。     

运动序列的时空结构特征表示模型

运动序列是一种与运动信号相关的多维时间序列,各个维度序列之间具有高耦合性的特点。现有的多维序列表征方法大多基于维度间相互独立的假设或缺乏可解释性,为此,提出一种适用于运动序列的时空结构特征表示模型及其两阶段构造方法。首先,基于空间变化事件的转换方法,将多维时间序列变换成一维事件序列,以保存序列中的空间结构特性。接着,定义了一种时空结构特征的无监督挖掘算法。基于新定义的表示度度量,该算法从事件序列中提取一组具有代表性的低冗余变长事件元组为时空结构特征。在多个人类行为识别数据集上的实验结果表明,与现有多维时间序列表示方法相比,新模型的特征集更具代表性,在运动序列模式识别领域可以有效提升分类精度。