粗糙集理论的核心内容是知识约简。
Rough set theory is the core content of knowledge reduction.
知识约简是粗糙集理论的重要研究内容。
Knowledge reduction is one of important issues in rough set theory.
提出新的条件信息熵及其高效知识约简算法。
A new conditional entropy and knowledge reduction algorithms are proposed.
知识约简是粗糙集理论研究中的重要内容之一。
Knowledge reduction is one of the important contents in the research on rough set theory.
提出一种基于互信息和疑义度相结合的知识约简方法。
A method of knowledge reduction based on the combination of mutual information and doubtful measure is proposed in this paper.
知识约简后决策表的条件熵等于初始决策表的条件熵。
The conditional entropy of decision table will not change in the reduction process.
最佳知识约简问题是信息系统与知识发现中面临的一个重要问题。
A problem in the information system and knowledge discovery, is a problem of processing optimal knowledge reduction.
目前，许多学者对知识约简做了深入的研究，并取得了很多成果。
At present, many scholars have made deep studies of knowledge reduction and achieved a lot.
在此基础上提出了优化的知识约简算法，该算法的时间复杂度是多项式的。
Accordingly, this paper offered optimized algorithm for reduction of knowledge, of which time complexity was polynomial.
本文提出图表示下的知识约简，给出图表示下求最小约简的完备递归算法。
A complete recursive algorithm for minimal reduction under graph view is designed.
给出基于模糊信任测度和模糊似然测度的随机模糊信息系统知识约简的方法。
The knowledge reduction method based on fuzzy belief measures and fuzzy plausibility measures are introduced.
简要介绍了粗糙集理论中区分矩阵算法和HORAFA算法在知识约简中的应用。
In this paper, application about discernibility matrix arithmetic and HORAFA arithmetic based on the rough set theory is introduced.
提出了一种基于条件信息熵的知识约简启发式算法，并指出该算法的时间复杂度是多项式的。
A heuristic algorithm based on conditional information entropy for knowledge reduction is proposed, and the complexity of this algorithm is analyzed.
建立武器参数效能模型，首先要挑选特征参数，这里采用知识约简方法选择武器的特征参数。
How to select the character parameters of weapon system is the first place. The character parameters of weapon system are selected based on reduction of knowledge.
然而，知识约简离不开一系列的算法作支撑，包括判断属性的重要性、求核、属性约简和值约简等。
However, knowledge reduction is dependent on a series of supporting algorithms such as the calculation of attribute significance, finding core, attribute reduction and value reduction.
知识约简是其中的核心内容，是在保持分类能力基本不变的情况下，获得系统的约简属性和分类规则。
Knowledge reduction is the core of Rough set. It obtains the reduction attribute and classification rules while holding the ability of classification unchanged.
将基于相似优势关系的粗糙集模型引入不完备模糊决策系统中，对其中的知识约简与知识获取问题进行了研究。
Moreover, the similarity dominance-based rough set model is introduced into the incomplete fuzzy decision system for knowledge reduction and knowledge acquisition.
粗糙集理论是一种新型的数据挖掘和决策分析方法，利用粗糙集理论进行决策表的知识约简与决策规则挖掘已经成为研究热点。
Rough set theory is a new data mining and decision analysis method. Knowledge reduction and decision rule mining in decision table by using rough set theory has become a research hotspot.
粗糙集理论是一种新型的处理模糊和不确定知识的数学工具，它能在保持信息系统分类能力不变的前提下，有效地进行知识约简；
Rough sets theory is a new mathematical tool to deal with vagueness and uncertain, which can remove redundant information and seek for reduced decision tables effectively.
包括理论的提出，一些基本的概念，数据的约简，知识表达系统，属性的约简，决策逻辑和决策规则最小化等。
It includes the proposing of the theory, some relevant fundamental concepts, the reduction of data and attributes, KRS, decision analysis, and the reduction of decision rules.
属性约简要求在保持知识库的分类和决策能力不变的条件下，删除不相关或不重要的属性。
Under the condition of unchanged classification and decision abilities, attribute reduction is to delete irrelative or unimportant attribute.
一方面分析了动态自主知识获取问题中的决策表动态约简问题，确定了在获得基本最小规则集后动态增加或减少规则的算法。
Dynamic reduction problem is discussed and algorithm adding and reducing rules in the decision-making table dynamically are put foreword so as to reduce the computing complexity.
知识发现的过程包括时间序列数据预处理、属性约简和规则抽取三部分。
The process of knowledge discovery in time series includes preprocessing of time series data, attributes reduction and rules extraction.
为此，设计了一种面向个性化知识发现的属性约简算法。
So a reduction algorithm of attribute for personalized knowledge discovery was designed.
属性约简是知识获取中的关键问题之一。
Attribute reduction is one of the key problems for the knowledge acquisition.
属性约简是知识获取中最重要的部分之一。
Attribute reduction is one of the most important parts in knowledge acquisition.
提出一种基于遗传算法的知识相对约简算法。
A kind of knowledge relative reduction Algorithm was proposed.
其次，设计了一个基于本文提出的基于相容关系的分配约简遗传算法的高校人事不完备信息系统的知识获取模型。
Secondly, a knowledge acquisition model for the incomplete information systems for the university personnel system on the basis of the tolerance relation assignment reduction using GA is designed.
应用属性约简规则处理数据可有效识别冗余知识，找出关键属性；
By using attribute reduction rule, it can distinguish the redundant knowledge and effectively discover key attributes.
应用属性约简规则处理数据可有效识别冗余知识，找出关键属性；
By using attribute reduction rule, it can distinguish the redundant knowledge and effectively discover key attributes.
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