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海量数据
    Methods Usiny modeling way to solve large data real-time display is only way.
    方法基于四叉树的鄂尔多斯盆地地形三维实时细节层次模型(LOD)表示的方法,从建模的角度来解决海量数据地形的实时显示问题。
    A Novel Classification Method in Large Data
    一种新的海量数据分类方法
    The Large Data Direct Classifying Method Based on Hyper Surface
    基于超曲面的海量数据直接分类方法
    In recent years, Data Mining has rosed a great attention of the information industry, the main reason is because data ocean has more and more larghe we need new technology to transmute the very large data into useful information or knowledge.
    近年来,数据挖掘(Data Mining)引起了信息产业界的极大关注,其主要原因是数据海洋的日益增大,我们需要新技术将海量数据转化为有用的信息和知识。
    Density Biased Sampling And Its Applications Research in Large Data Sets
    密度偏差抽样及其在海量数据挖掘中的应用
    Large dimensional random matrix is a popular research topic in the probability and statistics. Recently, as the computer science develops and the information blasts, we need to deal with large data sets with high dimensions in many fields.
    大维随机矩阵是概率统计领域的一个重要研究课题,近年来,随着计算机的发展和信息爆炸,在许多学科中都面临高维(上百或成千上万)和海量数据的处理问题。
    What is more, the river networks hydro- dynamic and quality integrate analysis system is developed by advanced Object-Oriented method. So large data can be show as kinds of Stat lines or table, and theory base is provided for river network water contamination control and environment management.
    应用先进的面向对象的编程语言,设计了河网水量水质综合分析系统,使海量数据可以形象直观的显示为各种统计曲线、图表,为河网水环境的污染控制及管理提供了理论依据。
    Then finding the information from large data that the users can be interested in has beenattracting more and more attention.
    那么从这些海量数据中找到使用者感兴趣的信息逐渐成为人们关注的焦点。
    Data Mining Technology, a tool that can discover information and knowledge in large data set, is used many fields, including anomaly detection.
    数据挖掘是帮助人们在海量数据中发现信息和知识的工具,广泛应用到各个领域,包括异常检测。
    Clustering is a branch of data mining applied in many fields such as statistics of large data、 analysis of network、 automatic supervisory of medical images.
    聚类是重要的数据挖掘技术,在海量数据统计、网络分析及医学图形图像自动监测等领域具有广泛的应用背景。
    How to design and implement large data spatial overlay method based on the object-relational data model as well as keeping the advantage of the model is an important and hot technique problem in spatial data model and algorithmic research.
    因此,如何在保留对象关系模型的优势的同时,设计实现对象关系数据模型框架下的海量数据空间叠加方法,是当前空间数据模型和算法研究亟待解决的重要技术问题。
    Because the marine data have the complicated spatio-temporal characteristics and comparatively the research of MGIS emerges recently. In result, there are some problems and difficulty on the manipulation of marine information when using traditional GIS, such as the basic expression of the marine spatio-temporal data, the storage of the large data set, and a series of questions to transmit the large data set and to display the dynamic data, and so on.
    由于海洋具有时空变化复杂性的特点,以及MGIS的研究起步比较晚,使得应用GIS处理海洋信息仍然存在一些问题和难点,如海洋时空数据的基本表达问题、海量数据的存储问题以及海量数据传输和海洋动态数据显示等一系列问题。
    Facing the rapid incensenient of large data collection, enterprises should have potent data analysis tools to transform the "fluent data" into "valuable knowledge", otherwise, large data will become "fluent data without useful information", what we call "data grave".
    面对快速增长的海量数据收集,企业必须要有有力的数据分析工具将“丰富的数据”转换成“有价值的知识”,否则大量的数据将成为“数据丰富,但信息贫乏”的“数据坟墓”。
    Especially on Internet, because of the restrict of the Internet bandwidth , how to transmit these large data becomes restricting the putting out of GIS information.
    特别是在Internet上,由于受到网络带宽的制约,海量数据的传输更是成了制约动态和实时发布GIS信息的瓶颈。
    Because data type is complex and data form is various, we design a mighty and friendly interface for users and achieve the storage and operation for large data, taking SQL Server 2000 as the background database and taking good use of the interface technology of Delphi.
    针对面波数据类型复杂,形式多样的特点,作者以SQL Server 2000作为后台数据库,充分利用Delphi接口技术,为用户开发出一个功能强大、友好的界面,实现了对海量数据的存储和操作。
    Data Mining technique is developing with the necessary of analyzing large data, it develop the technique of dealing large data into higher technology which contents find the relationship of all data, draw the characters of data and make a decision for consumer.
    数据挖掘技术是随着人们对海量数据的分析需求而逐步发展壮大的,它把对海量数据的处理从原始的检索应用发展到了更高一个层次,即发现数据之间的关联和规律,找出数据的特征,并提供给用户作出决策。
    A data warehouse provides a storage platform for large data, and the OLAP technology provides a method to analyze them.
    其中,数据仓库提供了一个存储海量数据的平台,OLAP技术提供了对数据分析的手段。
    For a professional business website,not only efficient and reliable data and operation management,but also quick and accurate searches for large data are needed.
    对于专业商务Web网站 ,既要求高效、可靠的数据管理和业务管理 ,又需要对海量数据进行快速、准确的检索。
    It is quite difficult to classify large data by using the support vector machine.
    使用支持向量机对海量数据的分类是相当困难的 .
    With CY3681 development board and its matching development software, the author designs the hardware and software and implements speedy transfers of large data with USB2.0 interface in large-scale and high-property scanner.
    利用此开发板和配套软件,在硬件和软件方面进行设计开发,实现了USB2.0接口在大幅面高性能扫描仪中快速传输海量数据的功能。
 

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