With respect to the multiple attribute decision making problems with linguistic preference relations on alternatives in the form of incomplete linguistic judgment matrix, a method is proposed to analyze the decision p...With respect to the multiple attribute decision making problems with linguistic preference relations on alternatives in the form of incomplete linguistic judgment matrix, a method is proposed to analyze the decision problem. The incomplete linguistic judgment matrix is transformed into incomplete fuzzy judgment matrix and an optimization model is developed on the basis of incomplete fuzzy judgment matrix provided by the decision maker and the decision matrix to determine attribute weights by Lagrange multiplier method. Then the overall values of all alternatives are calculated to rank them. A numerical example is given to illustrate the feasibility and practicality of the proposed method.展开更多
This paper proposes,from the viewpoint of relation matrix,a new algorithm of attribute reduction for decision systems.Two new and relative reasonable indices are first defined to measure significance of the attributes...This paper proposes,from the viewpoint of relation matrix,a new algorithm of attribute reduction for decision systems.Two new and relative reasonable indices are first defined to measure significance of the attributes in decision systems and then a heuristic algorithm of attribute reduction is formulated.Moreover,the time complexity of the algorithm is analyzed and it is proved to be complete.Some numerical experiments are also conducted to access the performance of the presented algorithm and the results demonstrate that it is not only effective but also efficient.展开更多
The class of multiple attribute decision making （MADM） problems is studied, where the attribute values are intuitionistic fuzzy numbers, and the information about attribute weights is completely unknown. A score fun...The class of multiple attribute decision making （MADM） problems is studied, where the attribute values are intuitionistic fuzzy numbers, and the information about attribute weights is completely unknown. A score function is first used to calculate the score of each attribute value and a score matrix is constructed, and then it is transformed into a normalized score matrix. Based on the normalized score matrix, an entropy-based procedure is proposed to derive attribute weights. Furthermore, the additive weighted averaging operator is utilized to fuse all the normalized scores into the overall scores of alternatives, by which the ranking of all the given alternatives is obtained. This paper is concluded by extending the above results to interval-valued intuitionistic fuzzy set theory, and an illustrative example is also provided.展开更多
According to the aggregation method of experts＇ evaluation information in group decision-making,the existing methods of determining experts＇ weights based on cluster analysis take into account the expert＇s preferen...According to the aggregation method of experts＇ evaluation information in group decision-making,the existing methods of determining experts＇ weights based on cluster analysis take into account the expert＇s preferences and the consistency of expert＇s collating vectors,but they lack of the measure of information similarity.So it may occur that although the collating vector is similar to the group consensus,information uncertainty is great of a certain expert.However,it is clustered to a larger group and given a high weight.For this,a new aggregation method based on entropy and cluster analysis in group decision-making process is provided,in which the collating vectors are classified with information similarity coefficient,and the experts＇ weights are determined according to the result of classification,the entropy of collating vectors and the judgment matrix consistency.Finally,a numerical example shows that the method is feasible and effective.展开更多
The ranking problem is studied when the pairwise comparisons values are unoertain in the analytic hierarchy process （AHP）. The method of constructing the judgment matrix is presented when the pairwise comparisons va...The ranking problem is studied when the pairwise comparisons values are unoertain in the analytic hierarchy process （AHP）. The method of constructing the judgment matrix is presented when the pairwise comparisons values are denoted by the unascertained three-valued reciprocal scales. By turning the reciprocal judgment matrix into attribute judgment matrix, the method to check the consistency of the pairwise comparisons judgment matrix and the calculation method of weighting coefficients are given. Finally, numerical examples are given to illustrate the effectiveness of the proposed method.展开更多
动态属性网络的语义社区发现及演化分析具有重要研究价值,其包含动态社区发现、社区语义解释及社区演化分析三个任务,但现有方法均难以同时实现.针对该问题,提出一种基于联合非负矩阵分解的方法DANNMF(NMF for Dynamic Attributed Netwo...动态属性网络的语义社区发现及演化分析具有重要研究价值,其包含动态社区发现、社区语义解释及社区演化分析三个任务,但现有方法均难以同时实现.针对该问题,提出一种基于联合非负矩阵分解的方法DANNMF(NMF for Dynamic Attributed Networks).DAN-NMF可以统一集成网络拓扑结构信息、节点属性信息及社区演化平滑约束信息,并利用最大最小化优化框架推导相关因子矩阵的迭代更新规则,从而可以直接获得动态社区发现、社区语义解释及社区演化分析结果.在人工合成和真实的动态属性网络进行大量相关实验,结果表明DAN-NMF比最优的基准方法在准确性指标上至少提高了7.3%.此外,在真实动态属性网络上的相关数据分析结果也表明DAN-NMF能够有效地发现动态社区的演化模式,并提供丰富的社区语义解释.展开更多
基金the National Natural Science Foundation of China (70701008)National Science Foundationfor Distinguished Young Scholars of China (70525002)
文摘With respect to the multiple attribute decision making problems with linguistic preference relations on alternatives in the form of incomplete linguistic judgment matrix, a method is proposed to analyze the decision problem. The incomplete linguistic judgment matrix is transformed into incomplete fuzzy judgment matrix and an optimization model is developed on the basis of incomplete fuzzy judgment matrix provided by the decision maker and the decision matrix to determine attribute weights by Lagrange multiplier method. Then the overall values of all alternatives are calculated to rank them. A numerical example is given to illustrate the feasibility and practicality of the proposed method.
基金supported by grants from the National Natural Science Foundation of China(No.70861001)the Natural Science Foundation of Hainan Province in China(No.109005).
文摘This paper proposes,from the viewpoint of relation matrix,a new algorithm of attribute reduction for decision systems.Two new and relative reasonable indices are first defined to measure significance of the attributes in decision systems and then a heuristic algorithm of attribute reduction is formulated.Moreover,the time complexity of the algorithm is analyzed and it is proved to be complete.Some numerical experiments are also conducted to access the performance of the presented algorithm and the results demonstrate that it is not only effective but also efficient.
基金supported by the National Science Fund for Distinguished Young Scholars of China(70625005).
文摘The class of multiple attribute decision making （MADM） problems is studied, where the attribute values are intuitionistic fuzzy numbers, and the information about attribute weights is completely unknown. A score function is first used to calculate the score of each attribute value and a score matrix is constructed, and then it is transformed into a normalized score matrix. Based on the normalized score matrix, an entropy-based procedure is proposed to derive attribute weights. Furthermore, the additive weighted averaging operator is utilized to fuse all the normalized scores into the overall scores of alternatives, by which the ranking of all the given alternatives is obtained. This paper is concluded by extending the above results to interval-valued intuitionistic fuzzy set theory, and an illustrative example is also provided.
文摘According to the aggregation method of experts＇ evaluation information in group decision-making,the existing methods of determining experts＇ weights based on cluster analysis take into account the expert＇s preferences and the consistency of expert＇s collating vectors,but they lack of the measure of information similarity.So it may occur that although the collating vector is similar to the group consensus,information uncertainty is great of a certain expert.However,it is clustered to a larger group and given a high weight.For this,a new aggregation method based on entropy and cluster analysis in group decision-making process is provided,in which the collating vectors are classified with information similarity coefficient,and the experts＇ weights are determined according to the result of classification,the entropy of collating vectors and the judgment matrix consistency.Finally,a numerical example shows that the method is feasible and effective.
文摘The ranking problem is studied when the pairwise comparisons values are unoertain in the analytic hierarchy process （AHP）. The method of constructing the judgment matrix is presented when the pairwise comparisons values are denoted by the unascertained three-valued reciprocal scales. By turning the reciprocal judgment matrix into attribute judgment matrix, the method to check the consistency of the pairwise comparisons judgment matrix and the calculation method of weighting coefficients are given. Finally, numerical examples are given to illustrate the effectiveness of the proposed method.
文摘动态属性网络的语义社区发现及演化分析具有重要研究价值,其包含动态社区发现、社区语义解释及社区演化分析三个任务,但现有方法均难以同时实现.针对该问题,提出一种基于联合非负矩阵分解的方法DANNMF(NMF for Dynamic Attributed Networks).DAN-NMF可以统一集成网络拓扑结构信息、节点属性信息及社区演化平滑约束信息,并利用最大最小化优化框架推导相关因子矩阵的迭代更新规则,从而可以直接获得动态社区发现、社区语义解释及社区演化分析结果.在人工合成和真实的动态属性网络进行大量相关实验,结果表明DAN-NMF比最优的基准方法在准确性指标上至少提高了7.3%.此外,在真实动态属性网络上的相关数据分析结果也表明DAN-NMF能够有效地发现动态社区的演化模式,并提供丰富的社区语义解释.
