fuzzy preference造句
例句与造句
- information aggregation based on fuzzy preference relations
模糊性偏序关系上的信息融合 - at the moment, how to define some particular preference structures reasonably is unresolved . the key problem is how to choose the transitivity properties . the research can serve as a guidance to define fuzzy preference structures
此外，如何合理地定义各种模糊偏好结构目前还是一个悬而未决的问题，其中许多偏好结构的定义将不可避免的涉及如何选择传递性性质问题。 - 3 . under the fuzzy preference, study on the aggregation of individual preference, and prove that even when the individual preferences are exact and the social preference is fuzzy, the different definitions we choose and the different results of social choice we can get
对模糊偏好的集结进行的研究，并证明了就是在极强的条件下，即允许个人偏好是非模糊的，而社会偏好是模糊的，随相关定义的选取不同，社会选择的结果也不同。 - thirdly, based on our definition of fuzzy preference structure without incomparability, we find out relationships between transitivity properties of large preference relation and strict preference and indifference relation with ^-transformation of lukasiewicz t-norm . for example, we point out that the w-transitivity of large preference relation can derive the same transitivity of strict preference and indifference relation
在作者所给出的模糊偏好结构定义的基础上，在无不可比关系的条件下以及lukasiewicz，模的尹变换叽的意义下，讨论了大偏好、严格偏好及无区别关系之间的传递性性质的联系，例如我们指出了大偏好关系的叽传递性可导出严格偏好以及无区别关系的叽传递性等。 - fuzzy relation theory is one of the most important branches of fuzzy mathematics and is extensively used in many fields especially in the area of decision-making . for example, fuzzy clustering analysis, choice problem under fuzzy preferences, ordering of fuzzy quantities and fuzzy preference structures are all based on fuzzy relations
模糊关系是模糊理论最重要的内容之一，其应用十分广泛；尤其是在模糊决策的许多领域中，如模糊聚类分析、模糊选择、模糊量排序、模糊偏好结构等，其研究都是建立在模糊关系基础之上的。 - It's difficult to find fuzzy preference in a sentence. 用fuzzy preference造句挺难的
- fuzzy relation theory is one of the most important branches of fuzzy mathematics and is extensively used in many fields especially in the area of decision-making . for example, fuzzy clustering analysis, choice problem under fuzzy preferences, ordering of fuzzy quantities and fuzzy preference structures are all based on fuzzy relations
模糊关系是模糊理论最重要的内容之一，其应用十分广泛；尤其是在模糊决策的许多领域中，如模糊聚类分析、模糊选择、模糊量排序、模糊偏好结构等，其研究都是建立在模糊关系基础之上的。 - abstract : an integrated approach is proposed to investigate the fuzzy multi-attribute decision-making ( madm ) problems, where subjective preferences are expressed by a pairwise comparison matrix on the relative weights of attributes and objective information is expressed by a decision matrix . an eigenvector method integrated the subjective fuzzy preference matrix and objective information is proposed . two linear programming models based on subjective and objective information are introduced to assess the relative importance weights of attributes in an madm problem . the simple additive weighting method is utilized to aggregate the decision information, and then all the alternatives are ranked . finally, a numerical example is given to show the feasibility and effectiveness of the method . the result shows that it is easier than other methods of integrating subjective and objective information
文摘:研究了结合主观和客观信息的模糊多属性决策问题,其中主客观信息分别由属性权重的两两比较矩阵和决策矩阵组成.提出一种结合主观和客观信息的特征向量决策方法,给出了2种求解基于主客观特征向量法的模糊多属性决策方法.这种方法通过求解2个线性目标规划模型得到最优属性权重,然后,通过对决策信息进行简单的加权集结,得到所有方案的排序结果.最后,通过一个算例说明了该方法的实用性和有效性.结果表明,该方法要比其他主客观结合多属性决策方法简单 - we investigate the decision-making problem with a finite set of alternatives, in which the decision information takes the form of a fuzzy preference relation . we develop a simple and practical approach to obtaining the priority vector of a fuzzy preference relation . the prominent characteristic of the developed approach is that the priority vector can generally be obtained by a simple formula, which is derived from a quadratic programming model . we utilize the consistency ratio to check the consistency of fuzzy preference relation . if the fuzzy preference relation is of unacceptable consistency, then we can return it to the decision maker to reconsider structuring a new fuzzy preference relation until the fuzzy preference relation with acceptable consistency is obtained . we finally illustrate the priority approach by two numerical examples . the numerical results show that the developed approach is straightforward, effective, and can easily be performed on a computer
研究了决策信息以模糊偏好关系给出的有限方案决策问题,提出了一种简洁且实用的模糊偏好关系排序方法.该方法首先建立一个二次规划模型,然后基于该模型推导出求解模糊偏好关系排序向量的一个简洁公式.基于获得的排序向量,利用一致性比例对模糊偏好关系进行一致性检验.对于一致性较差的模糊偏好关系,则需反馈给决策者重新进行判断,直至得到一个一致性可接受的模糊偏好关系为止.最后,利用2个算例对该方法进行分析和说明,数值结果表明该方法简洁、有效,且易于在计算机上操作 - we investigate the decision-making problem with a finite set of alternatives, in which the decision information takes the form of a fuzzy preference relation . we develop a simple and practical approach to obtaining the priority vector of a fuzzy preference relation . the prominent characteristic of the developed approach is that the priority vector can generally be obtained by a simple formula, which is derived from a quadratic programming model . we utilize the consistency ratio to check the consistency of fuzzy preference relation . if the fuzzy preference relation is of unacceptable consistency, then we can return it to the decision maker to reconsider structuring a new fuzzy preference relation until the fuzzy preference relation with acceptable consistency is obtained . we finally illustrate the priority approach by two numerical examples . the numerical results show that the developed approach is straightforward, effective, and can easily be performed on a computer
研究了决策信息以模糊偏好关系给出的有限方案决策问题,提出了一种简洁且实用的模糊偏好关系排序方法.该方法首先建立一个二次规划模型,然后基于该模型推导出求解模糊偏好关系排序向量的一个简洁公式.基于获得的排序向量,利用一致性比例对模糊偏好关系进行一致性检验.对于一致性较差的模糊偏好关系,则需反馈给决策者重新进行判断,直至得到一个一致性可接受的模糊偏好关系为止.最后,利用2个算例对该方法进行分析和说明,数值结果表明该方法简洁、有效,且易于在计算机上操作 - we investigate the decision-making problem with a finite set of alternatives, in which the decision information takes the form of a fuzzy preference relation . we develop a simple and practical approach to obtaining the priority vector of a fuzzy preference relation . the prominent characteristic of the developed approach is that the priority vector can generally be obtained by a simple formula, which is derived from a quadratic programming model . we utilize the consistency ratio to check the consistency of fuzzy preference relation . if the fuzzy preference relation is of unacceptable consistency, then we can return it to the decision maker to reconsider structuring a new fuzzy preference relation until the fuzzy preference relation with acceptable consistency is obtained . we finally illustrate the priority approach by two numerical examples . the numerical results show that the developed approach is straightforward, effective, and can easily be performed on a computer
研究了决策信息以模糊偏好关系给出的有限方案决策问题,提出了一种简洁且实用的模糊偏好关系排序方法.该方法首先建立一个二次规划模型,然后基于该模型推导出求解模糊偏好关系排序向量的一个简洁公式.基于获得的排序向量,利用一致性比例对模糊偏好关系进行一致性检验.对于一致性较差的模糊偏好关系,则需反馈给决策者重新进行判断,直至得到一个一致性可接受的模糊偏好关系为止.最后,利用2个算例对该方法进行分析和说明,数值结果表明该方法简洁、有效,且易于在计算机上操作 - we investigate the decision-making problem with a finite set of alternatives, in which the decision information takes the form of a fuzzy preference relation . we develop a simple and practical approach to obtaining the priority vector of a fuzzy preference relation . the prominent characteristic of the developed approach is that the priority vector can generally be obtained by a simple formula, which is derived from a quadratic programming model . we utilize the consistency ratio to check the consistency of fuzzy preference relation . if the fuzzy preference relation is of unacceptable consistency, then we can return it to the decision maker to reconsider structuring a new fuzzy preference relation until the fuzzy preference relation with acceptable consistency is obtained . we finally illustrate the priority approach by two numerical examples . the numerical results show that the developed approach is straightforward, effective, and can easily be performed on a computer
研究了决策信息以模糊偏好关系给出的有限方案决策问题,提出了一种简洁且实用的模糊偏好关系排序方法.该方法首先建立一个二次规划模型,然后基于该模型推导出求解模糊偏好关系排序向量的一个简洁公式.基于获得的排序向量,利用一致性比例对模糊偏好关系进行一致性检验.对于一致性较差的模糊偏好关系,则需反馈给决策者重新进行判断,直至得到一个一致性可接受的模糊偏好关系为止.最后,利用2个算例对该方法进行分析和说明,数值结果表明该方法简洁、有效,且易于在计算机上操作 - we investigate the decision-making problem with a finite set of alternatives, in which the decision information takes the form of a fuzzy preference relation . we develop a simple and practical approach to obtaining the priority vector of a fuzzy preference relation . the prominent characteristic of the developed approach is that the priority vector can generally be obtained by a simple formula, which is derived from a quadratic programming model . we utilize the consistency ratio to check the consistency of fuzzy preference relation . if the fuzzy preference relation is of unacceptable consistency, then we can return it to the decision maker to reconsider structuring a new fuzzy preference relation until the fuzzy preference relation with acceptable consistency is obtained . we finally illustrate the priority approach by two numerical examples . the numerical results show that the developed approach is straightforward, effective, and can easily be performed on a computer
研究了决策信息以模糊偏好关系给出的有限方案决策问题,提出了一种简洁且实用的模糊偏好关系排序方法.该方法首先建立一个二次规划模型,然后基于该模型推导出求解模糊偏好关系排序向量的一个简洁公式.基于获得的排序向量,利用一致性比例对模糊偏好关系进行一致性检验.对于一致性较差的模糊偏好关系,则需反馈给决策者重新进行判断,直至得到一个一致性可接受的模糊偏好关系为止.最后,利用2个算例对该方法进行分析和说明,数值结果表明该方法简洁、有效,且易于在计算机上操作 - we investigate the decision-making problem with a finite set of alternatives, in which the decision information takes the form of a fuzzy preference relation . we develop a simple and practical approach to obtaining the priority vector of a fuzzy preference relation . the prominent characteristic of the developed approach is that the priority vector can generally be obtained by a simple formula, which is derived from a quadratic programming model . we utilize the consistency ratio to check the consistency of fuzzy preference relation . if the fuzzy preference relation is of unacceptable consistency, then we can return it to the decision maker to reconsider structuring a new fuzzy preference relation until the fuzzy preference relation with acceptable consistency is obtained . we finally illustrate the priority approach by two numerical examples . the numerical results show that the developed approach is straightforward, effective, and can easily be performed on a computer
研究了决策信息以模糊偏好关系给出的有限方案决策问题,提出了一种简洁且实用的模糊偏好关系排序方法.该方法首先建立一个二次规划模型,然后基于该模型推导出求解模糊偏好关系排序向量的一个简洁公式.基于获得的排序向量,利用一致性比例对模糊偏好关系进行一致性检验.对于一致性较差的模糊偏好关系,则需反馈给决策者重新进行判断,直至得到一个一致性可接受的模糊偏好关系为止.最后,利用2个算例对该方法进行分析和说明,数值结果表明该方法简洁、有效,且易于在计算机上操作 - an integrated approach is proposed to investigate the fuzzy multi-attribute decision-making ( madm ) problems, where subjective preferences are expressed by a pairwise comparison matrix on the relative weights of attributes and objective information is expressed by a decision matrix . an eigenvector method integrated the subjective fuzzy preference matrix and objective information is proposed . two linear programming models based on subjective and objective information are introduced to assess the relative importance weights of attributes in an madm problem . the simple additive weighting method is utilized to aggregate the decision information, and then all the alternatives are ranked . finally, a numerical example is given to show the feasibility and effectiveness of the method . the result shows that it is easier than other methods of integrating subjective and objective information
研究了结合主观和客观信息的模糊多属性决策问题,其中主客观信息分别由属性权重的两两比较矩阵和决策矩阵组成.提出一种结合主观和客观信息的特征向量决策方法,给出了2种求解基于主客观特征向量法的模糊多属性决策方法.这种方法通过求解2个线性目标规划模型得到最优属性权重,然后,通过对决策信息进行简单的加权集结,得到所有方案的排序结果.最后,通过一个算例说明了该方法的实用性和有效性.结果表明,该方法要比其他主客观结合多属性决策方法简单