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  1. 在ROLLUP中需要适当地排列维的属性,确保数据正确地在每个级上聚合。

    The attributes of the dimension will need to be arranged appropriately in the ROLLUP to ensure data is correctly aggregated at each level .

  2. 根据我医生的建议时,我迟疑地试图维甲酸在高剂量和强有力的,但什么也没有发生。

    Based on my doctor 's recommendation , I hesitantly tried Accutane in high and strong dosages , but nothing happened .

  3. 结果IPF算法能够很好地拟合高维表的模型,并得出了合理的结果。

    Results IPF algorithm could effectively fit the model for high way table and give a reasonable interpretation .

  4. Ridgelet变换是继小波变换之后提出的一种新的多尺度变换,它能比小波变换更好地表达高维线性奇异性。

    The ridgelet transform is a new directional multi-resolution transform , which is more suitable for describing signals with high dimensional singularities .

  5. 应用软琼脂集落形成法选出单克隆HL-60细胞系,系统地研究新维甲类化合物R81001的分化诱导作用。证明该药可使人早幼粒白血病细胞的NBT还原能力明显增强,呈浓度依赖性。

    By using soft agar colony-forming assay , a monoclonal subline of human promyelocytic leukemia HL-60 cells was isolated and inducing activity of differentiation of a new retinoid R-81001 on the cells was studied .

  6. 并开发了用于检验六维鼠标控制功能的虚拟6-SPS并联机器人系统,同时成功地将六维鼠标用于微操作机器人控制系统中。

    The thesis develops virtual 6-SPS parallel robot system to test the mouse 's control functions . The 6-DOF mouse has been used in micromanipulator robot system successfully .

  7. 因此,本文提出了基于投影寻踪回归的文本自动分类算法,通过投影寻踪回归算法,可以真实地描述高维数据的客观内在规律,从而达到降低特征维数,提高文本分类的精度的目的。

    We propose a Text classification model based on Projection Pursuit Regression .

  8. 此算法结合由底向上的网格划分方法和自顶向下的网格划分方法,能快速、有效地处理高维数据流。

    This algorithm combines the bottom-up grid partition method and top-down grid partition method .

  9. 我们必须要重视并理解如何更好地运用2维图形(剪影)去表达自己的想法。

    We must focus on understanding how to best use2 dimensional shapes to express ideas .

  10. 在高维空间中,由于数据的稀疏性,传统的聚类方法难以有效地聚类高维数据。

    It is hard to cluster high-dimensional data using traditional clustering algorithm because of the sparsity of data .

  11. 该方法既较好地避免了维灾难问题,又能自适应地得到某种形式的收敛结果。

    This method can not only avoid the dimension disaster , but also can receive convergence results adaptively .

  12. 实验结果表明该改进微粒群算法可以有效地解决高维数值优化问题。

    The simulation results show that the improved PSO algorithm can solve the high-dimensional numerical optimization problem effectively .

  13. 多尺度几何分析方法具有各向异性特征,能够有效地表示高维数据空间中的线奇异和面奇异。

    MGA has the characteristics of anisotropy , and it can approach a high dimensional function containing line singularity effectively .

  14. 基于混沌神经网络模型可以有效地解决高维、离散、非凸的非线性约束优化问题。

    The Chaotic neural network model can be used to solve many multi-dimensioned , discrete , non-convex , nonlinear constrained optimization problems .

  15. 另一方面它能很好地处理高维数据和大数据集的数据表格。

    Besides , it performs well when dealing with high dimensional data and has good scalability when the size of the data sets increases .

  16. 试验表明这一装置可以满意地测量两维平面振动,亦可用于两维平面运动的测量。

    The test shows that two dimensional planar vibration as well as the movement in two dimensional plane can be satisfactorily measured by thin device .

  17. 新算法应具有处理速度快、对孤立点不敏感等优点,可以有效地在高维数据流中识别出子空间聚类。

    It should have high efficiency and should not be sensitive to outliers and can find clusters in subspaces from high dimensional data stream effectively .

  18. 本文将首次把伪随机序列分析中常用的采样及折叠方法,系统地引入高维最佳2元阵列的研究之中,并得到了一些新结果。

    In this paper , we introduce the methods of sampling and folding to the study of perfect binary arrays ( shortened as PBA ) .

  19. 流形学习是一种新的非监督学习方法,可以有效地发现高维非线性数据集的内在维数和进行维数约简,近年来越来越受到机器学习和认知科学领域研究者的重视。

    As a new unsupervised learning technique , manifold learning has captured the attention of many researchers in the field of machine learning and cognitive sciences .

  20. 这些特点使有效地解决高维问题成为可能,因为内积运算是可以用原空间中的核函数实现的,我们甚至不必要知道变换的形式。

    These characteristics make it possible to overcome problems among high-dimensional , because inner product operation can be achieved from the function of the original space , which even do not need form transformation .

  21. 为此建立了多方向投影寻踪算法,以便求出多个投影寻踪方向,更精确地在低维空间中表现原始数据的空间分布规律。

    An algorithm of multi direction projection pursuit is constructed to calculate multi directions of projection pursuit , the high dimensional data of hyperspectral remote sensing can be represented on a lower dimensional space more accurately .

  22. 核方法是近年发展起来的一种新的机器学习方法,它可在高维(特征)空间中用线性的方法有效地解决低维(输入)空间中线性不可分问题。

    Kernel method has been of wide concern in the field of machine learning recently . It allows the efficient computation of linear classification in high-dimensional feature space , instead of non-linearly separable problem in low-dimensional input space .

  23. 新方法的特点是程序简单,可以较精确地求解10维以下的等式或不等式约束问题,无需提供偏导数。

    This method is featured by simple procedure , accurate solution of equality or inequality constraints not more than 10.No partial derivative is required and the calculations will decreased by tens or hundreds of times as compared with the conventional random test .

  24. 该算法用基于近似相对熵的实码遗传优化投影寻踪方法(RCGOA-PP),有效地将高维数据中隐藏的目标信息集中投影到低维空间中,并用直方图分割的方法提取出小目标。

    This algorithm uses approximate entropy index 's Projection Pursuit based on Real Coding Genetic Optimize Algorithm ( RCGOAPP ) to project the targets information hided in the high-dimensional data into low-dimensional space and then extract small targets with histogram image segmentation method .

  25. 流形学习是模式识别中的基本方法,它以非监督的形式,可以有效地发现高维数据分布的内在几何结构,挖掘隐藏在高维数据中的本征信息与内在规律,实现维数约简。

    Manifold learning is the basic method of pattern recognition . It can effectively find the internal distribution of high-dimensional geometry data in the form of unsupervised , and find the intrinsic information and internal laws hidden in high-dimensional data to achieve dimensionality reduction .

  26. 局部线性嵌入算法(LocalLinearEmbedding,简称LLE)是一种非线性流形学习算法,能有效地学习出高维采样数据的低维嵌入坐标,但也存在一些不足,如不能处理稀疏的样本数据。

    The local linear embedding algorithm is a nonlinear manifold learning algorithm . It is efficient for many nonlinear dimension reduction problems but unfit for sparse data .

  27. 本论文的主要目的是分类有限维的Hopf代数,特别地去分类有限维的基本Hopf代数。

    The main aim of this paper is to classify finite dimensional Hopf algebras , especially basic Hopf algebras .

  28. 该算法将对一个MK维的整体寻优转化为K次M维的向量寻优,从而能够显著地降低由于高维状态所带来的计算复杂度。

    This algorithm transform M K-dimension global optimization into K times of M-dimension vector optimization . So the computing complexity brought by high-dimension state decreases evidently . 3 .

  29. 2%夫西地酸乳膏联合维胺脂胶囊治疗寻常痤疮疗效观察

    Clinical observation on acne vulgaris with 2 % Fusidic acid cream and Viaminate capsules

  30. 地勘工程3维空间数据模型及其数据结构设计

    Design of Three-Dimensional Spatial Data Model and Its Data Structure in Geological Exploration Engineering