1) Measure of Majority Inclusion
多数包含度
2) majority inclusion relation
多数包含关系
1.
To make up for the drawbacks of general relations of rough set model, a majority inclusion relation is defined.
通过分析一般关系下基本粗糙集模型的不足,定义了一般关系下的多数包含关系,借助引入的 误差参数α(0≤α<1/2),给出了一般关系下的变精度粗糙集模型。
3) Including Polymorphism
包含多态
1.
The paper analyses 4 mechanisms about polymorphism actualizing, which contains Compulsory Polymorphism, Overloading Polymorphism, Parameterized Polymorphism, Including Polymorphism.
本文结合例子,对强制多态,重载多态,参数类型化多态,包含多态这四种多态实现机制进行了分析,阐述了多态性在程序设计中的应用。
4) contain measure
包含测度
1.
The paper is concerned with two aspects:A necessary and sufficient condition for convex hull of a set in E2 being closed; Convex body and its contain measure.
本论文以凸体为研究对象,主要涉及两个方面的内容:平面凸集的凸包为闭集的充分必要条件;特殊凸体(椭圆)的包含测度。
5) Inclusion degree
包含度
1.
Intuitionistic fuzzy rough set based on inclusion degree;
基于包含度的直觉模糊粗糙集模型
2.
New reduction method based on inclusion degree in inconsistent decision table;
基于包含度的不一致决策表约简新方法
3.
Som e notes on strong inclusion degree;
强包含度公式的若干注记
6) including degree
包含度
1.
By including degree ,the conception of confidence degree of association rules are depicted and the relation between cinfidence degree and accuracy measure of Rough set are discussed .
通过包含度刻画了关联规则信任度概念及讨论了它与Roughset精度的关系,特别地通过包含度的性质推导了信任度的增量计算。
2.
In this paper, the concept of including degree is introduced and some methods of generating including degrees are given.
本文引进了包含度的概念以及包含度的生成方法,给出了包含度在专家系统中关于知识获取与推理的某些应用。
3.
As the uncertainty of inconsistent decision rules,combining the knowledge of inconsistent decision rules and the knowledge of whole table,the paper handle inconsistent decision rules based on including degree,and the effect is verified though an exemple.
鉴于不一致规则的不确定性,基于包含度这一描述不确定性关系的有效度量方法,综合不一致规则信息与整个决策表信息,对不一致规则进行修正,进而获取较理想的决策规则,并通过实例进行验证。
补充资料：大多数
1.超过半数很多的数量。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条