第五章研究了信息系统的约简算法。
In chapter five: The reduction algorithms of information system were studied.
将属性约简算法与其他算法结合在一起使用。
Connecting the improved attributes reduction algorithm with other algorithms.
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.
本文主要研究基于粗集理论的属性约简算法。
This paper researches attributes reduction of Rough Set Theory.
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.
有一个很好的实现动态并行约简算法调用内核？
Is there a good implementation of reduction algorithm callable from kernel with dynamic parallelism?
后面又提到了基于信息熵的相对属性约简算法。
And then a relative attribute reduction algorithm is mentioned based on information entropy.
给出了基于不可区分矩阵的属性频率约简算法。
Then, an attribute reduction algorithm based on indiscernibility matrix is introduced.
提出一种基于粗糙集属性重要性的属性约简算法。
Proposed an algorithm of attribute reduction based on attribute importance of rough set.
首先，研究了在不完备信息系统下的属性约简算法。
Firstly, the attributes reduction algorithm is studied under the incomplete information systems.
针对海量信息系统的约简问题提出了分层约简算法。
A hierarchical reduction algorithm is proposed to reduce a huge information system.
提出了一种基于决策属性支持度的属性相对约简算法。
A kind of attribute relative reduction for decision attribute support degree was proposed.
并在此基础上提出了基于差分演化算法的属性约简算法。
And on this basis, an attribute reduction algorithm based on the improved differential evolutionary algorithm was put forward.
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.
提出了一种基于模糊决策属性依赖度的属性相对约简算法。
A kind of attribute relative reduction for fuzzy decision attribute dependent degree is proposed.
进一步给出了有核信息系统与无核信息系统的分层约简算法。
The hierarchical reduction algorithms are then presented for both the information system with and without core attributes.
并提出改进的值约简算法，时间复杂度在原有基础上大大减少。
And putting forwarded the improved algorithm of value attribute reduction that decreases the complexity of time greatly.
因此研究准确、高效的约简算法具有极大的理论价值和现实意义。
The research of exact and effective data reduction algorithms based on Rough Set has greatly theoretical value and realistic meaning.
分层递阶约简算法在某水泥窑炉控制决策获取中的应用证实其有效性。
The application in acquiring the control decision of a cement kiln shows the validity of the hierarchical reduction approach.
首先分析对比较为成熟的属性约简算法的优缺点，提出论域缩减的方法。
Firstly, we put forward an improved domain reduction method on the basis of analyzing the attribute reduction algorithm of the current information system.
拓展算法三：引入统计筛选和线性判别分析相结合的分层递阶约简算法。
Extended approach three: a hierarchical reduction approach is imported, which is based on the combination of statistical feature selection and linear discriminant analysis.
传统的利用区分矩阵进行属性约简算法，其时间复杂度和空间复杂度很大。
The time complexity and space complexity of the traditional attribute reduction algorithm using discernible matrix are quite big.
为提高粗集约简的效率，提出了一种基于条件信息量的快速粗集约简算法。
To improve the efficiency of attribute reduction, a rapid reduction algorithm based on conditional information quantity is proposed.
本文模拟人类认知的分层递阶原则，提出一种粗糙集理论的分层递阶约简算法。
Simulating the hierarchical principle of human cognizance process, a hierarchical reduction algorithm of rough set theory is proposed in this paper.
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.
与现有的决策表属性约简算法进行比较，它具有较低的复杂度和较强的可使用性。
Comparing with the old attribute reduction algorithms, it has lower complex degree and has powerful usability.
编程实现了对故障决策表的约简，测试结果证明了谚约简算法的有效性和可用性。
Finally, the reduction of fault diagnosis decision-table by the program is achieved and the results show the effectiveness and usefulness of the approach by testing the concrete example.
再次，对有序决策表进行了研究，提出了一种基于优势矩阵的启发式属性约简算法。
After that we study on the ordered decision table and propose a new heuristic attribute reduction algorithm based on dominance matrix, whose time complexity is polynomial.
再次，对有序决策表进行了研究，提出了一种基于优势矩阵的启发式属性约简算法。
After that we study on the ordered decision table and propose a new heuristic attribute reduction algorithm based on dominance matrix, whose time complexity is polynomial.
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