• Using an attribute Matrix view in Rational RequisitePro (see Figure 4), you can view all or a select subset of use cases and their respective attributes.

    使用RationalRequisitePro中的Attribute MatrixView(如图4所示),你可以查看所有的或者一组选定的用例及它们各自的属性。

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  • Create the attribute, traceability matrix, and traceability tree views as necessary.

    根据需要创建属性、可追溯矩阵和可追溯树视图。

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  • Based on the reduction of attribute sets, the partial order relation matrix of radar jamming space is obtained.

    在计算属性约简集的基础上,建立了雷达干扰空间的偏序关系矩阵。

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  • Finally, the equivalence properties between Boolean matrix representation and algebra representation of attribute reduction are proved.

    最后证明了属性约简在布尔矩阵和代数两种不同表示下是等价的。

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  • The time complexity and space complexity of the traditional attribute reduction algorithm using discernible matrix are quite big.

    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。

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  • Then, we present an improved decision matrix together with a method for attribute reduction of the decision table and an example shows that the improved method is effective and complete.

    然后给出一个改进的决策矩阵和属性约简方法,例子分析表明,改进后的方法是有效的和完备的。

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  • This paper analyses attribute value reduction, and presents a method to acquire briefest rules directly by constructing decision matrix in consistent decision table.

    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。

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  • Based on classify criterion matrix, single-valued whitenization weight function and reliability code, grey attribute recognition clustering method is put forward.

    运用分类标准矩阵、单指标白化权函数和置信度原则,提出了基于属性识别的灰色聚类方法。

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  • Then, an attribute reduction algorithm based on indiscernibility matrix is introduced.

    给出了基于不可区分矩阵的属性频率约简算法。

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  • For the sake of the limitation of product effect of the Probability-Effect Matrix, the paper adopts the Ideal Point Method which is often used in Multiple Attribute Decision Making.

    在数量合成方法的选取上,为了克服传统的风险矩阵方法中乘积效应的缺陷,文章引入了在多属性决策中常用的理想点方法。

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  • Based on attribute measure, the concepts of related attribute measure and attribute judgment matrix are presented.

    在属性测度基础上,提出了相对属性测度和属性判断矩阵的概念。

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  • Based on the definitions, the core finding algorithm, the relative attribute reduction algorithm and value reduction of information decision system are presented based on binary discernibility matrix.

    在定义的基础上,给出了基于二进制区分矩阵的求核算法、相对属性约简算法及值约简算法。

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  • 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。

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  • Based on attribute measurement, attribute hierarchical model is established by analyzing judgment criterion and attribute judgment matrix.

    在属性测度的基础上,通过分析判断准则和属性判断矩阵,建立了属性层次模型。

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  • The Improved judgment matrix analytical method was used to calculate the attribute values of the objects, which was projected to the unit coordinate axis to be standardized.

    利用改进的判断矩阵分析法计算对象的属性值,并向单位坐标轴投影进行标准化。

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  • The attribute adjacent graphics and the interrelated matrix for edge and face of variation feature were given. The organic relation between component faces of variation feature was expressed.

    给出了变异特征属性邻接图和边面关联矩阵,表达了变异特征组成面之间的有机联系。

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  • Using attribute recognition theory and according to the measurement attribute of objective data in power quality indices, the index measurement evaluation matrix (MEM) is built.

    利用属性识别理论,根据电能质量指标客观数据的测度属性建立指标测度评价矩阵。

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  • Following analysing the traits of the prime attribute in relation schema, an algorithm based on matrix to solve the prime problem is proposed in this paper.

    本文从分析主属性在关系模式中的特点出发,在模式矩阵及其分类的基础上,给出了一个基于矩阵的关系模式主属性的判定算法。

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  • In the application of the attribute hierarchical model, it is necessary to test the uniformity of the attribute judgment matrix.

    在属性层次模型的应用中,要检验属性判断矩阵的一致性。

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  • The author gains insights from attribute reduction based on discernability matrix and proposes a few rough-set based text feature selection algorithms, i. e. , DB1, DB2 and LDB.

    作者从基于分辨矩阵的粗糙集属性约简中受到启发,提出了一系列基于粗集理论的文本特征选择算法,即DB1、DB2、LDB。

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  • And three modified attribute reduction algorithms are presented, including modified algebraic algorithm, weighed sum of attribute significance algorithm and modified discernible matrix algorithm.

    提出了三种改进的属性约简算法:改进的代数集合算法、重要度加权平均算法和改进的可辨识矩阵算法。

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  • In incomplete information system, objects of the tolerance class and maximal consistent block in the attribute reduction algorithm based on discernibility matrix are uncertain.

    在不完备信息系统基于差别矩阵的属性约简算法中,相容类和最大相容类中的对象具有不确定性。

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  • Related weights and synthetic weights can easily be obtained from attribute judgment matrix.

    相对权重和合成权重很容易从属性判断矩阵获得。

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  • Both of attribute weight frequency and strong compressible set are used to simplify discernibility matrix so that computing complexity is decreased and reduction efficiency is.

    同时利用属性加权频率和强等价集概念化简区分矩阵,既减小了计算复杂度又提高了约简效率。

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  • Both of attribute weight frequency and strong compressible set are used to simplify discernibility matrix so that computing complexity is decreased and reduction efficiency is increased.

    同时利用属性加权频率和强等价集概念化简区分矩阵,既减小了计算复杂度又提高了约简效率。

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  • This paper studies the multi-attribute decision making problem, in which the decision information takes the form of triangular fuzzy number complementary judgement matrix.

    研究了决策信息以三角模糊数互补判断矩阵形式给出的多属性决策问题。

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  • In order to solve updating core attributes of incremental condition attribute system, an equivalent binary discernibility matrix is proposed based on in-depth study firstly.

    为解决信息系统在条件属性动态增加情况下的核属性更新问题,通过深入分析得到了一种二进制区分矩阵的等价表示方法;

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  • The purpose of this paper is to study multi-attribute decision making on the basis of consistency of fuzzy complementary judgment matrix.

    论文主要研究基于模糊互补判断矩阵一致性的多属性决策问题。

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  • Then the membership matrix obtained by clustering algorithm was used to reduce attribute set. Finally, based on entropy, a knowledge acquisition method of fuzzy Rough Set (RS) was put forward.

    进而将聚类得到的属性隶属矩阵用于属性约简,并提出一种基于信息熵的模糊粗糙集知识获取的方法。

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  • Then the membership matrix obtained by clustering algorithm was used to reduce attribute set. Finally, based on entropy, a knowledge acquisition method of fuzzy Rough Set (RS) was put forward.

    进而将聚类得到的属性隶属矩阵用于属性约简,并提出一种基于信息熵的模糊粗糙集知识获取的方法。

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