提出了一种新型的决策规则约简方法。
A method of reduction of decision rulers is proposed based on rough set and fuzzy set.
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.
粗糙集理论的概念性框架之一就是利用不可分辨关系和布尔推理作为数据约简和获取决策规则的基础。
Rough sets theory provides a framework in which indiscernibility relations and Boolean reasoning form a foundation for data reduction and decision rule generation.
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.
然后在属性值约简中进一步去除与用户无关的属性，从而抽取个性化决策规则。
Secondly, during reduction of attribute values, some irrelevant attributes are further eliminated, then abstractation of personalized decision rules is accomplished.
改进了一种粗糙集决策表的值约简算法，并将其应用到文本分类规则的提取中。
A reduction algorithm based on rough set is improved and then applicated to extract the rules of text categorization.
但是属性约简是一个NP问题，对属性的约简和决策规则的约简只能通过启发式算法实现。
But the attribute reduction is a NP problem, the attribution reduction and decision rule reduction will be solved by method of elicitation.
基于粗糙集方法提出了一种系统的决策表约简和决策规则提取方法。
Based on the rough set theory, a new systematic method is proposed to reduce the decision table and induce the decision-making rules.
最后应用粗糙集理论来对决策信息表进行离散化处理和属性约简，以生成图像分割算法选取的决策规则。
Finally, rough set theory is applied to discretization and attribution reduction of decision information table, in order to make the decision rule of image segmentation algorithm selection.
该文分析属性值约简，针对协调决策表提出一种通过构造决策矩阵直接获取最简规则的方法。
This paper analyses attribute value reduction, and presents a method to acquire briefest rules directly by constructing decision matrix in consistent decision table.
最后，建立了一个利用约简决策表的距离图求决策规则的核值及最小决策算法的算法框架。
At last, applying the distance graph of the reduced decision table, we propose a way to get the core of each decision rule.
粗糙集中决策表约简也就是以基于最少的条件属性和最小冗余的属性值导出最少的决策规则或分类规则。
Simplification of Decision tables in Roouh set is order to lead decision rule or categorised rule at the least on the basis of the least condition attribute and minimum redundant attribute value.
通过属性约简和值约简，找出影响成型质量的关键因素，从而得到判断成型结果的决策规则。
The key factors affecting the quality of molding were detected through attribute reduction and value reduction, and the decision rules important to control the molding results were thus obtained.
新的约简模型将满足平均决策强度条件的最简规则集作为最终的约简结果，解决了不相容决策表约简结果不一致的问题。
The most concise decision rule set that satisfies condition of mean decision power is regarded as final reduction result in the new reduction model.
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.
同时，借助决策矩阵进行值约简，提出了一种新的规则提取算法，使最终得到的决策规则更加简洁。
Furthermore, a new algorithm for rule extraction based on decision matrices was presented. And much more concise decision rules could be got with this method.
给出了数据约简方法，包括建立RS知识模型、RS决策逻辑表示、确定辨识矩阵、计算其核心、进行属性归约、规则形成等内容。
Information reduction method is given, in which includes RS knowledge modeling, RS decision logic expression, distinction matrix making, cores calculation, attributes reduction, rules generation, etc.
新的算法对生成的带频度属性的决策规则进行约简处理，得出最简决策规则。
The new algorithm carries out the reduction processing to the generated decision rules containing the frequency attribute and obtains the simplest decision rules.
以粗糙逻辑为基础，首先给出了在新实例加入论域后判断约简变化与否以及判断原极小决策算法中决策规则变化与否的判定依据。
Based on rough logic, theorems is presented, whether attribute reduction and minimal decision algorithm change or not when a new instance is added to the universe.
包括数据的分类，KRS的建立，数据的约简和决策规则的生成。
It shows how to classify the data, build the KRS, reduce the data and get the final decision rules.
本论文的研究工作，主要围绕着基于粗糙集理论的动态约简以求得决策规则。
The research of this thesis is mainly about the dynamic reduction based on rough set theory as well as how to establish and develop the decision rules after completing the reduction.
文中从实际诊断中出发首次将IEC- 60599三比值故障诊断表编写成对应的逻辑编码表，然后应用粗糙集理论构造决策表并对决策表进行约简，最后建立改进的新导则IEC - 60599三比值故障诊断决策规则。
Firstly, a logical diagnostic table of IEC-60599 is presented, and a decision table can be constructed by applying the Rough Set Theory based on the IEC-60599 three-ratio fault diagnosis table.
粗糙集理论的主要思想是在保持分类能力的前提下通过属性约简和值约简提取的决策规则。
The main idea of rough set theory is to extract decision rules by attribute reduction and value reduction in the premises of keeping the ability of classification.
对此，对拥有6个属性（4个条件和两个决策属性）以及10 2个个体的一致决策表或邻域值决策表进行处理并生成了约简的决策规则。
Thus, reduction of the tables is handled to possess 6 attributes (4 conditional attributes and 2 decision attributes) and 102 objects to use two methods respectively, and to obtain the same results.
对此，对拥有6个属性（4个条件和两个决策属性）以及10 2个个体的一致决策表或邻域值决策表进行处理并生成了约简的决策规则。
Thus, reduction of the tables is handled to possess 6 attributes (4 conditional attributes and 2 decision attributes) and 102 objects to use two methods respectively, and to obtain the same results.
应用推荐