1) relativized minimality
相对最简性
2) relative minimal reduction
相对最小约简
1.
The practical results show that the approach is effective and the complete relative minimal reduction in each class of the information system are obtained.
针对粗糙集理论中不完备信息系统的容差关系的一种改进模型,结合遗传算法的全局优化和隐含并行性的特性,给出了一种不完备信息系统属性约简方法,经仿真实验知该算法是有效的,能得到不同概念层次的所有相对最小约简。
3) relative attribute reduct
相对属性约简
1.
We study in this paper relations between absolute and relative attribute reducts of an information table.
研究信息表绝对属性约简与相对属性约简之间的关系,指出一个绝对属性约简通常只是包含而不一定会是相对属性约简,同时给出相对属性约简不是绝对属性约简的一个充分条件。
4) relativistic degeneracy
相对论简并性
5) relative reduction
相对约简
1.
The influence of the necessary attributes after class subdivision on the upper and lower approximate values,quality and accuracy of approximate classification,number of decision-making rules and relative reduction are analyzed theoretically.
针对粗糙集的决策系统,给出了有效等价类细化和有效集合细化的定义,从理论上分析了必要属性细化后对上近似和下近似、近似分类精度和质量以及决策规则的数量和相对约简的影响。
2.
By means of the methodology of rough set,different attribute classification methods for decision systems are first analyzed in this paper,and the attribute significance as well as the extremely small subset of the attribute relative reduction caused by a classification variety is discussed.
应用粗糙集的方法,分析决策系统中不同的属性分类方法,以及不同分类方法引起的属性重要性与属性相对约简极小子集的变化情况,寻求属性分类方法与属性约简结果相互影响的内在因素,给出高效的属性分类方法和合理确定约简子集的策略,生成策略对应软件的实现算法,并运用软件实现算法来选取相对约简子集。
3.
Two parameters for different level partitions (or similar degree between objects) α,β are used in these reductions, in which the positive region formula of the decision level set are adopted for relative reduction and importance degree of attributes, and the distributed reducti.
这些约简利用了2个水平划分参数(或对象相似度)α、β,其中相对约简与属性重要性度量采用了决策类的水平集正区域公式。
补充资料：连续性与非连续性(见间断性与不间断性)
连续性与非连续性(见间断性与不间断性)
continuity and discontinuity
11an父ux泊g四f“山。麻以角g、.连续性与非连续性(c。nt，n琳t:nuity一)_见间断性与不间断性。and diseo红ti-
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