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大数据
    SYSTEM DESIGN AND REALIZATION FOR TRANSMITTING LARGE DATA BY SATELLITE
    大数据卫星传输系统的设计与实现
    The PC-cluster computers are widely applied to the seismic data processing and interpretation with large data volume, and the hardware structure and the system management are more complicated.
    PC Cluster集群计算机在大数据量的地震资料解释处理中应用比较广泛,其硬件结构和系统管理比较复杂。
    The computation results show that parallel genetic algorithm is fit for data reduction problem with large scale and large data sample point.
    计算结果表明,并行遗传算法适合于求解问题规模较大及大数据样本点的数据约简问题。
    The Large Data Center's Backup strategy and Implementation
    大数据中心的数据备份策略及实现
    The Design and Application of Large Data Analysis Software
    超大数据空间的软件设计与应用
    Using Prefetching to Improve Web Application User Experience in a Large Data Environment
    利用预取技术改善Web应用程序在大数据量环境中的用户体验
    Results show that parallel genetic algorithm is fit for data reduction problem with large scale and large data sample point.
    结果表明,并行遗传算法适合于求解问题规模较大及大数据样本点的数据约简问题.
    A METHOD OF REALLZING LARGE DATA AMOUNT TWO DIMENSIONAL FFT WITH THE HELP OF MAGNETIC DISC
    利用磁盘实现大数据量二维快速付里叶变换的方法
    A Method of Dealing with Large Data Based on Data Buffering
    一种基于文件缓冲方式的操作大数据量数据的方法
    In the fourth chapter, for extreme value distribution, Weibull distribution and other conventional distribution population, the detection statistic of unusually large data is constructed and the large sample approximate distribution is investigated.
    在第四章,对极值分布、威布尔分布等其它一些常见分布总体,构造了检测异常大数据的检验统计量,并研究了相应的大样本近似分布分布。 异常观测数据处理及不确定大系统的鲁棒镇定四川大学博士学位论文
    4. Large data processing was relatively well solved by means of compiling and running of expression evaluation and code optimization.
    4 通过表达式求值的编译执行和代码优化等手段,较好地解决了大数据量的处理问题。
    It had obvious advantages in basic data operation such as copy and paste etc, especially in the condition of large data.
    即使对一些基本的数据操作,如拷贝、粘贴等,在大数据量时,也具有非常明显的优势。
    Due to the high complexity of spatial objects and spatial queries and also due to extremely large spatial data volumes, currently Geographic Information System (GIS) is faced with stringent requirements on large data storage, efficient access method and fast query processing.
    由于空间数据本身的复杂性,以及目前对海量空间数据快速查询的要求日益提高,当前地理信息系统正面临着大数据量空间数据存储及管理的挑战。
    On the other hand,,RST has the features of handling and reducing large data sets while has lower classification accuracy than SVMs.
    粗集理论则具有处理和约简大数据量的优势,但分类精度不如SVM方法。
    Depth image-based rendering for geometry models gives another compensation for traditional geometry-based rendering techniques with its faster rendering,independent of geometry complexity and needing less computing resource,So it is very valuable for simplifying very large data geometry models and displaying them in real time.
    基于深度图像的几何模型绘制从另一个角度弥补了传统基于几何绘制技术的不足,它绘制速度更快、与模型复杂度无关而且对资源要求更少,因而对于大数据量几何模型的简化和实时三维仿真具有重要的研究价值。
    By adding data samples of same type, we have solved one contradiction in application of Self-organizing Data Mining algorithm: its Analog Complexing algorithm needs large data samples while there are only narrow data samples in complex economy system.
    使用增加同类经济对象数据样本的方法,解决了自组织数据挖掘算法实际应用的一个矛盾:其相似体合成算法需要大数据样本但复杂经济系统中有效数据样本不足。
    However, a detailed point cloud surface usually causes large data size and takes a long time to transmit through the network.
    然而高密度点云曲面带来的大数据量,给点云曲面模型的存储及传输都带来了问题。
    We conclude that cache-oblivious algorithms do outperform traditional RAM-model algorithms when working on large data sets.
    本文的主要结论是,当处理大数据量时,高速缓存参数无关算法显著优于传统的基于RAM模型的算法。
    In order to get the data better and truly, many data verification technology are also introduced to the system, such as parity code, financial system checkout, large data checkout, the relation of data checkout.
    为了得到高质量的财务报表数据,保证数据的准确性,系统采用了校验码、财务制度校验、大数据校验、数据钩稽关系校验等多种数据校验技术。
    The clients and server communicate with each other through network socket, for each time translating date from client to server, there are two copy process: first from client buffer to kernel space, then from kernel space to server space. This will result in large system expense problem, especially when translating large data.
    Nano-X的客户进程和服务器通过网络套接字进行通讯,一次数据传输需要经过从客户缓存区到核心空间,再从核心空间到服务器空间的两次拷贝过程,这种方式带来系统开销较大,特别是传送大数据量时效率较低的问题。
 

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