• Effective data discretization can obviously improve system ability on clustering instances, and can also make systems more robust to data noise.

    有效的离散化可以显著地提高系统对样本的聚类能力,增强系统对数据噪音的鲁棒性。

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  • The discretization of BIE is based upon constant elements.

    边界积分方程的离散基于常数元模式。

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  • FEM requires a discretization (a mesh or a model) of a domain.

    FEM需要对域进行离散化(一个网格或者模型)。

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  • Simulated results show this discretization error cannot be neglected.

    模拟计算结果表明,该离散化误差不能忽略。

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  • Improve a greedy algorithm for discretization of continuous attribute.

    改进了连续属性离散化的贪心算法。

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  • The discretization of continuous properties is very important in data mining.

    连续属性的离散化在数据挖掘中有着非常重要的作用。

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  • A data preprocessing method based on multi continuous attribute discretization.

    基于多连续属性离散化的数据预处理方法。

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  • Given the stability, error estimate of full discretization for the linear equation.

    给出该线性方程全离散的稳定性和误差估计。

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  • The cell centered finite volume method is used as the spatial discretization method.

    空间上应用中心平均的有限体积法进行离散。

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  • In one embodiment, the parameters are preprocessed by discretization of the parameters.

    在一个实施例中,参数通过参数的离散化被预处理。

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  • The discretization and relevant numerical technique for the equation are briefly described.

    简述了方程的离散化及有关的数值技术。

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  • The finite volume discretization method and treatment of boundary condition were presented.

    采用有限容积法离散方程,附加源项法处理边界条件。

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  • In the data integration stage of KDD, data discretization is one of the most important jobs.

    在KDD的数据集成阶段,数据离散化是其中一件非常重要的工作。

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  • The discretization of real value attributes is one of the most main problems in rough sets theory.

    连续属性的离散化是粗糙集理论的主要问题之一。

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  • Then the author's researches on data discretization and attribute reduction are introduced in detail.

    随后论文重点对作者在数据离散和属性约简两个方面做的研究工作进行了阐述。

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  • The new method can realize the discretization of multiple features and converge to the preset conflict level.

    该方法可以自动实现多特征的离散化操作,并且收敛到预设的冲突水平上。

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  • This paper presents a cluster method for discretization in the processing of mining quantitative association rules.

    应用聚类方法研究了数量关联规则提取过程中的连续属性离散化问题。

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  • Numerical scattering is one of the most common discretization errors in the numerical method for radiative transfer equation.

    数值散射是辐射传递方程近似算法中最常见的离散误差。

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  • Current model is the key part in the rotor flux linkage oriented control system, and its discretization analysis is conducted.

    电流模型是转子磁链定向控制的关键,这里对其进行了离散化分析。

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  • By analyzing the differential equation for GM(1,1), this paper deduces one accurate discretization model to solve GM(1,1) model.

    通过分析GM(1 ,1 )模型白化形式微分方程的解析表达式,导出了求解GM( 1 ,1 )的精确离散化模型。

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  • In order to overcome the problem, a new method of data discretization based on candidate cuts discernibility matrix is presented.

    针对这一问题,提出了一种基于候选断点区分矩阵的数据离散化算法。

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  • This paper gets discretization equation by integrating the basic equation of unsteady heat conduction and writes a calculating program.

    此文根据非稳定热传导基本方程式积分得到离散化方程式,编写出计算程序。

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  • Because the curves always cannot be discretized completely pursuant to the given criterions, the discretization rules must be modified.

    由于曲线往往不能够按要求被完全离散,因此需要对离散原则进行调整。

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  • This paper introduces a polygon discretization technique into the network model decomposition method to solve waveguide eigenvalue problems.

    本文将多边形离散技术引入网络模型分解法中,用来求解波导特征值问题。

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  • Using regular grid for discretization results in diffraction noise for dip interface, and infilling grid may increase the computing efforts.

    采用规则网格进行离散,对于倾斜界面无法避免绕射噪声,若加密网格又过度增加工作量。

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  • Since it is an inverse problem, numerical techniques, such as discretization of the integral into a system of linear equations, are necessary.

    由于这是一个反问题,一些数字技术比如将积分离散化为一个线性方程组是必需的。

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  • Finally, the algorithm can improve the basic global discretization method, and is tested on the soil sorts data of agricultural expert system.

    该方法改进了基本的整体离散化算法,并利用农业专家系统中的土壤分类数据对算法进行了验证。

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  • Finally, the algorithm can improve the basic global discretization method, and is tested on the soil sorts data of agricultural expert system.

    该方法改进了基本的整体离散化算法,并利用农业专家系统中的土壤分类数据对算法进行了验证。

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