一种新的多层次关联规则挖掘算法

关联是数据挖掘领域的一个重要研究课题。如何有效地推导出关联规则,在过去已经有许多方法相继被提出,但大部分的方法对于(a)数值型数据的处理、(b)渐进式挖掘以及(c)在线挖掘等问题无法有效地同时加以处理。因此本文通过对多层次关联规则的研究,提出了以模糊分割与数据方阵为基础的算法来解决上述问题。     

空间数据立方体多维信息空间分析实例*

多维信息空间分析是构筑数字城市最为关键的技术之一,而空间数据立方体是解决这个关键技术问题的有效途径;提出了空间数据立方体的分析操作主要由概括分析、局部分析、全局分析和旋转分析组成,简单介绍了这些分析操作功能和结构;在分析操作过程中,采用具体分析功能和例子数据相结合的直观方式列举了多维信息的缓冲区分析、连接分析、网络分析实例.     

Spatial correlation-based characterization of acoustic emission signal-cloud in a granite sample by a cube clustering approach

To extract more in-depth information of acoustic emission(AE) signal-cloud in rock failure under triaxial compression, the spatial correlation of scattering AE events in a granite sample is effectively described by the cube-cluster model. First, the complete connection of the fracture network is regarded as a critical state. Then, according to the Hoshen-Kopelman(HK) algorithm, the real-time estimation of fracture connection is effectively made and a dichotomy between cube size and pore fraction is suggested to solve such a challenge of the one-to-one match between complete connection and cluster size. After, the 3D cube clusters are decomposed into orthogonal layer clusters, which are then transformed into the ellipsoid models. Correspondingly, the anisotropy evolution of fracture network could be visualized by three orthogonal ellipsoids and quantitatively described by aspect ratio. Besides, the other three quantities of centroid axis length, porosity, and fracture angle are analyzed to evaluate the evolution of cube cluster.The result shows the sample dilatancy is strongly correlated to four quantities of aspect ratio, centroid axis length, and porosity as well as fracture angle. Besides, the cube cluster model shows a potential possibility to predict the evolution of fracture angle. So, the cube cluster model provides an in-depth view of spatial correlation to describe the AE signal-cloud.     

论城市设计的基本构架

文章从理论上探讨了城市设计的基本问题,提出了“城市设计立方体”的概念,对城市设计与城市建设管理一体化做了粗浅讨论,以期通过这样的工作框架,把城市设计成果的效力最大限度地发挥出来。     

Parallel solution of arbitrarily sparse linear systems

A parallel algorithm for the iterative solution of sparse linear systems is presented. This algorithm is shown to be efficient for arbitrarily sparse matrices. Analysis of this algorithm suggests that a network of Processing Elements [PE's] equal in number to the number R of non-zero matrix entries is particularly useful. If this collection of PE's is interconnected by a message-passing, or a synchronous, communication network which is fast enough, the iteration time grows as the logarithm of the number of PE's. A comparison with earlier work, which suggested that only √R PE's are useful for this task, is also presented. The performance of three proposed networks of PE's on this algorithm is analyzed. The networks investigated all have the topology of the Cube Connected Cycles [CCC] graph, and all employ the same silicon technology, and the same number of chips and wires, and hence all should cost the same. One, the Boolean Vector Machine [BVM], employs 2²⁰ bit-serial PE's implemented in 4096 VLSI chips; the other two networks use different 32-bit parallel microprocessors, and a 32-bit parallel CCC to interconnect 2048 2-chip processors. One of the microprocessors is assumed to deliver about 1 Mflop, while the other is assumed to deliver 32 Mflops per PE. The comparison indicates that the BVM network would have superior performance to both of these parallel networks.     

High Performance OLAP and Data Mining on Parallel Computers

On-Line Analytical Processing (OLAP) techniques are increasingly being used in decision support systems to provide analysis of data. Queries posed on such systems are quite complex and require different views of data. Analytical models need to capture the multidimensionality of the underlying data, a task for which multidimensional databases are well suited. Multidimensional OLAP systems store data in multidimensional arrays on which analytical operations are performed. Knowledge discovery and data mining requires complex operations on the underlying data which can be very expensive in terms of computation time. High performance parallel systems can reduce this analysis time. Precomputed aggregate calculations in a Data Cube can provide efficient query processing for OLAP applications. In this article, we present algorithms for construction of data cubes on distributed-memory parallel computers. Data is loaded from a relational database into a multidimensional array. We present two methods, sort-based and hash-based for loading the base cube and compare their performances. Data cubes are used to perform consolidation queries used in roll-up operations using dimension hierarchies. Finally, we show how data cubes are used for data mining using Attribute Focusing techniques. We present results for these on the IBM-SP2 parallel machine. Results show that our algorithms and techniques for OLAP and data mining on parallel systems are scalable to a large number of processors, providing a high performance platform for such applications.     

种基于OLAP的Cube存储结构

Cube计算对OLAP有着极其重要的作用。本文根据数据仓库模式的前端用户接口之一OLAP,设计了一个多维的超压缩立方体结构HierarchicalCompressCube(CHCube)HH,并详细讨论了它的创建、增量更新及快速查询算法。在创建CHCube结构时,充分利用了元数据信息,因而在OLAP查询及更新等操作上具有很好的时空有效性。在实际的OLAP应用系统中,使得对多维数据的描述更加灵活,对多维数据的操作更加高效。     

使用Delphi模拟多维数据分析的一种设计

文章提出了在关系数据表中模拟多维数据分析的一种方法，利用Delphi的决策支持组件Decision Cube来进行，并举例说明了如何使用这组控件进行多维数据分析。     

对体可视化Marching Cube算法的改进

提出一个由三维数据计算等值面中点的算法,它在两方面对标准Ｍａｒｃｈｉｎｇ Ｃｕｂｅ算法进行了改进。第一个改进是：在等值面上样本点的状态依赖于它所连接的边同等值面相交的数目;第二个改进是：两相邻样本点中等值面多边形顶点被定位于中点,使得共面三角片合并为一个多边莆,减少了生成多边形的数量,提高了算法效率。     

Monte Carlo methods for computing the capacitance of the unit cube

It is well known that there is no analytic expression for the electrical capacitance of the unit cube. However, there are several Monte Carlo methods that have been used to numerically estimate this capacitance to high accuracy. These include a Brownian dynamics algorithm [H.-X. Zhou, A. Szabo, J.F. Douglas, J.B. Hubbard, A Brownian dynamics algorithm for calculating the hydrodynamic friction and the electrostatic capacitance of an arbitrarily shaped object, J. Chem. Phys. 100 (5) (1994) 3821–3826] coupled to the “walk on spheres” (WOS) method [M.E. Müller, Some continuous Monte Carlo methods for the Dirichlet problem, Ann. Math. Stat. 27 (1956) 569–589]; the Green’s function first-passage (GFFP) algorithm [J.A. Given, J.B. Hubbard, J.F. Douglas, A first-passage algorithm for the hydrodynamic friction and diffusion-limited reaction rate of macromolecules, J. Chem. Phys. 106 (9) (1997) 3721–3771]; an error-controlling Brownian dynamics algorithm [C.-O. Hwang, M. Mascagni, Capacitance of the unit cube, J. Korean Phys. Soc. 42 (2003) L1–L4]; an extrapolation technique coupled to the WOS method [C.-O. Hwang, Extrapolation technique in the “walk on spheres” method for the capacitance of the unit cube, J. Korean Phys. Soc. 44 (2) (2004) 469–470]; the “walk on planes” (WOP) method [M.L. Mansfield, J.F. Douglas, E.J. Garboczi, Intrinsic viscosity and the electrical polarizability of arbitrarily shaped objects, Phys. Rev. E 64 (6) (2001) 061401:1–061401:16; C.-O. Hwang, M. Mascagni, Electrical capacitance of the unit cube, J. Appl. Phys. 95 (7) (2004) 3798–3802]; and the random “walk on the boundary” (WOB) method [M. Mascagni, N.A. Simonov, The random walk on the boundary method for calculating capacitance, J. Comp. Phys. 195 (2004) 465–473]. Monte Carlo methods are convenient and efficient for problems whose solution includes singularities. In the calculation of the unit cube capacitance, there are edge and corner singularities in the charge density distribution. In this paper, we review the above Monte Carlo methods for computing the electrical capacitance of a cube and compare their effectiveness. We also provide a new result. We will focus our attention particularly on two Monte Carlo methods: WOP [M.L. Mansfield, J.F. Douglas, E.J. Garboczi, Intrinsic viscosity and the electrical polarizability of arbitrarily shaped objects, Phys. Rev. E 64 (6) (2001) 061401:1–061401:16; C.-O. Hwang, M. Mascagni, Electrical capacitance of the unit cube, J. Appl. Phys. 95 (7) (2004) 3798–3802; C.-O. Hwang, T. Won, Edge charge singularity of conductors, J. Korean Phys. Soc. 45 (2004) S551–S553] and the random WOB [M. Mascagni, N.A. Simonov, The random walk on the boundary method for calculating capacitance, J. Comp. Phys. 195 (2004) 465–473] methods.