离散化

To solve this problem, new oblique hypersurface discretization method is presented.

连续属性的离散化是粗糙集理论的主要问题之一。

Discretization is a new method in this paper.

本次研究的主要方法是离散化和质点运动等，这也是本文的一个新方法，通过比较相关的资料，可以发现，这种方法是合适的，也是可行的。

Example analysis shows that, comparing with other discretization algorithms, the algorithm proposed in this paper is satisfactory.

实例分析表明，和其它离散化算法相比，本算法取得了较满意的结果。

The discretization of continuous attributes is one of the most main problems in applying of rough set theory.

连续属性离散化是粗集理论应用中面临的主要问题之一。

Discretization of continuous attributes is always one of the key problems that need urgent solutions in rough sets theory.

连续属性的离散化是粗糙集理论亟待解决的关键问题之一。

We gave discretization of continuous valued attributes based on interdependence of information system.

提出了基于系统最大依赖度的连续属性的离散化方法。

More importantly, difference equations also appear in the study of discretization methods for differential equations.

更重要地，在对微分方程的离散化方法的研究中也出现了差分方程。

In this paper a new discretization algorithm of continue attributes in decision table is offered.

该文提出一种新的决策表连续属性离散化算法。

It can be used for any kind of electromagnetic problems and guarantee convergence for a sufficiently dense discretization.

采用矩量方程可以很好的解决任何电磁问题，同时，也可以保证适合于充分离散化的收敛性。

It mainly carries on the continuous process stochastic differential equation discretization of the research.

技术上的思想主要是将连续过程的随机微分方程离散化来进行研究。

The split between the two groups can hardly be papered over.

这两个团体间的分歧难以掩饰。

This approach not only encourages a greater number of responses, but minimizes the likelihood of stale groupthink.

这种做法不仅鼓励了更多的反应，而且减少跟风的可能性。