Focused on a posteriori error estimates a finite volume discretization of an elliptic problem.

We present an appropriate compromise between two kind methods of discretization.

属性离散化的方法可以分为两类:局部方法和全局方法.

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In this paper a discretization algorithm based on importance of cut point.

提出一种基于断点重要性的离散化算法.

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So the discretization on the fine-grid space become linear.

这使得原问题在细网格上就变成了线性方程.

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Focused on a posteriori error estimates for a finite volume discretization of an elliptic problem.

引言有限元后验误差估计和超收敛性质在有限元计算中具有重要的实际意义.

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And the applications of solving the two mathematical models with the domain discretization BEM are studied.

研究了区域剖分边界元方法在求解这两类数学模型时的应用.

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Rough set theory has been successfully applied in data discretization.

粗集理论已经成功地应用于数据离散化.

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The triangular meshes of three dimensional curved surfaces are generated by development and discretization surfaces.

通过对曲面的扩展及离散,生成三维曲面的三角形网格.

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The governing equations are discretization with non-staggered grid by means of finite volume method.

介绍一种在非交错网格上,求解非正交曲线坐标系下的流动控制方程的方法.

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This paper proposes a new discretization algorithm for continuous attributes to incomplete information systems.

针对不完备信息系统提出了一种新的粗糙集离散化算法.

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However, the result is unsatisfactory when the correct discriminant rate only lies between 53-63 % .

惟其正确区别率仅在 53-63% 之间, 效果并不十分理想.

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Finally, the discriminant rate close to 90.

最后的判别正确率接近90%.

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Afternoon be concerned about the amount of energy change, discriminant rebound effort.

后市需关注量能变化, 判别反弹力度.

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Then, the features of the general discriminant must be relative to the law of structure change.

于是, 得到晋遍判别法的应有特征,其判别式也应有规律,且须与完备风网系列间的结构变化规律相对应.

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In order to save the expense, also can build a medical model by step discriminant analysis.

为了节省费用, 还可以运用多元统计中的逐步判别分析方法建立模型.

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The results showed the method of discriminant analysis was useful and the discriminant function was valid.

因此,所用的判别分析方法可行,建立的判别函数有效.

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Statistical techniques , including Multi-Regression, Cluster Analysis, and Discriminant Analysis , were employed to test ten null hypotheses.

本研究以世界银行发展报告书的统计为依据,共选定1970年、1975年 、 1980年 、 1985年、1990年、1995年各国高等教育在学率为分析资料.

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Linear Discriminant Analysis ( LDA ) is one of the classical and popular Methods: Used for feature extraction.

线性 鉴别 分析是特征抽取中最为经典和广泛使用的方法之一.

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Independent Component Analysis ( ICA ) and Linear Discriminant Analysis ( LDA ) are two effective methods of feature extraction.

本文提出了一种基于独立成分分析和线性鉴别分析的特征提取方法.

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Kernel linear discriminant analysis ( KLDA ) is essentially a nonlinear feature extraction criterion.

核线性判别准则 ( KLDA ) 是一种非线性特征提取准则.

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The discriminant analysis has an important significance for orebody classification.

判别分析对研究未知属性矿体的归属有着重要的意义.

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