查询词典 rough-headed

Rough ideals been first introduced by Kuroki N. Under the condition of the congruence relation, a rough set of a subsemigroup was proved to be its subsemigroup, while that of a leftideal was also proved to be its leftideal.

Kuroki N研究了半群中的粗理想，首次提出了粗子半群和粗理想的概念，证明了在同余关系下，半群的粗糙集是半群，左理想的粗糙集是左理想。

In this paper, granularity in rough set theory is used to describe rules based on the concept of rough degree. A tool for knowledge dependent relation diagram is put forward. Then dimensional knowledge granularity decision space and the same construction mapping decision space based on multi-decision sorts is established, and decision algorithm based on KDRD and decision space is introduced. Finally, through combining with the technique of fault diagnosis, it is proved that the approach is very appropriate to the intelligent decision system.

本文利用粗糙集理论中的粗度概念，在对获取规则进行扩展性的粒度描述的基础上，提出了一种工具―知识依赖关系图，构造了n维知识粒度决策空间以及基于多决策类的同构映射决策空间，建立了基于KDRD和决策空间的决策算法，并结合机械故障诊断说明了本方法非常适于故障诊断等通过结论获取原因的智能决策系统。

As the extension of rough set,variable precision rough set reflects the difference of degrees of overlap of kinds and sets.

而可变精度粗糙集作为对经典粗糙集理论的扩展，体现了等价类与集合的重叠度程度上的差别。

After a brief summary on data mining and rough set theory, the research works in the thesis can be descript as follows: 1. To the problem that finding rules in enormous data is very timeconsumable and the expansibility of existed algorithms is not very good, the thesis proposes a new method to discompose large data table based on the concepts of positive region and the importance of attribute in rough set theory.

Rough集理论是一种新型的处理不确定性知识的数学工具，围绕着数据挖掘领域存在的问题，本文利用Rough集理论与Rough分析工具，提出若干解决方案，同时在具体处理问题过程中引入了信息理论、因子分析等方法，与Rough分析结合使用，讨论了Rough集技术在知识发现、关联规则挖掘、模式分类以及数据清洗等问题中的应用。

Then, we study Rough Set Theory approach to KDD, develop two algorithms for deriving Reduct and propose the integration of domain knowledge into Rough Set Theory to mining multiple-level rules.

本文在分析了传统的关联规则挖掘算法的基础上，给出了几个挖掘算法和一个递增修正算法；提出了模糊关联规则的概念及其挖掘算法；研究了结合背景知识的多层次关联规则的挖掘方法。

Chapter 2 is started from the basic theory of elastodynamics, the zero and the first order reflection and transmission coefficients of rough interface are derived in theory, and some numerical examples are given. Also dispersion characters of diffraction waves are discussed in the case of micro-rough interface in deep layers.

第二章从弹性动力学的基本理论出发，通过求解波动方程的定解问题，从理论上导出了地震波在粗糙界面上的零阶和一阶反射透射系数，并给出了数值算例；该章还讨论了深层微粗糙界面的绕射波的频散特征。

The main procedures of the body are conducted as the following:First, this article reviewed the Rough Set elementary theory, the decision information system and the expansion of the Rough Set model.

本文的主要研究工作如下：首先，本文回顾了Rough集的基本理论、决策信息系统和Rough集模型的扩展。

The preparation process of equisetum pratense total alkaloid includes the following steps: coarse pulverizing equisetum pratense to obtain rough powder, methyl alcohol percolation to obtain percolate, recovering methyl alcohol, concentrating, degreasing by means of petroleum ether, alkalifying concentrate, CHCl3 extracting, soda lye washing, neutral water washing, recovering CHCl3 to obtain rough alkaloid, adsorption by using silica gel column, eluting, recovering solvent so as to obtain refined EPR.

该发明是通过两个步骤来实现的：第一步，提取草问荆总碱，流程：草问荆粗粉――渗漉液――浓缩液(析胶、石油醚脱脂、氨水碱化)――碱化浓缩液(CHCl3萃取)――CHCl3层――CHCl3液(回收CHCl3)――粗生物碱――吸附硅胶柱――精致EPR。第二步，选择实验试剂、仪器、用小鼠作为实验对象，进行中枢神经系统实验，研究作用及作用机制。

Based on rough set theory, research in this paper mainly focuses on mining rules from decision system.Based on the research of the basic concepts of rough set, we deeply analysis and discuss the approximation set algorithm, equivalence class algorithm, core algorithm, attribute reduction algorithm, rules extract algorithm etc.

本文首先对数据挖掘和知识发现作一概述，并论述了粗糙集理论的重要概念及其度量，基于这些概念和度量，具体分析了粗糙集理论的近似集算法、核算法、属性约简算法、规则提取算法，给出了它们的算法分析以及具体实现步骤。

Rough set theory and factor space are all applied worldly. The partition determined by equivalence relation is the same as knowledge in rough set theory, that is, knowledge is regarded as a partition of data.

粗糙集理论和因素空间在各个方面有着广泛的应用，由于粗糙集理论将等价关系对空间的划分与知识等同，即将知识理解为对数据的划分，任何U的子集称为U中的一个概念或范畴。

It was just a normal day of school

那只是上学的普通一天

Which is a very good reference in this issue.

这是一个在这个问题上很好的参考。