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基于模糊熵的直觉模糊多属性群决策方法 总被引:1,自引:0,他引:1
针对专家权重未知、专家判断信息以直觉模糊集给出的多属性群决策问题,提出了一种新的决策方法.通过定义直觉模糊集的模糊熵计算专家判断信息的模糊程度,进而确定每位专家的权重.然后定义直觉模糊集的模糊交叉熵确定备选方案距理想方案和负理想方案的距离,再根据加权算术算子集结专家的判断信息,得到方案的排序.最后,通过一个实例分析验证了方法的有效性. 相似文献
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《模糊系统与数学》2016,(4)
以熵理论为基础,针对属性权重和时间权重完全未知的动态多属性区间直觉模糊决策问题,首先针对现有区间直觉模糊熵公理化定义的缺陷进行了分析,提出一种改进的区间直觉模糊熵的公理化定义,并据此构造了区间直觉模糊熵的一个新的计算公式;其次,利用改进的区间直觉模糊熵确定属性权重;再次,基于时间度体现对近期数据的重视程度的基础上,利用时间权向量的信息熵为优化目标来确定时间权重;然后,利用区间直觉模糊几何加权算子进行集结,并利用区间直觉模糊集的排序函数对决策方案进行排序和择优。最后,通过一个实例分析,表明本文提出的方法的可行性和有效性,为动态多属性区间直觉模糊决策问题提供了一种新的方法和思路。 相似文献
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本文对区间直觉模糊信息的TOPSIS多属性决策方法进行了研究。在属性权重信息完全未知的情况下,通过研究熵权法以及区间直觉模糊集本身的一些性质特点,将熵权法拓展到区间直觉模糊环境中来确定属性权重,进而提供了一种可直接利用评估信息的新的TOPSIS决策方法。该方法不仅拓展了传统熵权法的应用范围,而且不需要决策者事先给出权重信息,结果更加客观和可靠。应用实例表明该方法的可行性和有效性,具有推广应用价值。 相似文献
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为更大程度的保留决策信息的原始性,针对决策过程决策信息的聚合、备选方案的比选问题,提出一种基于集成算子改进得分函数的区间直觉模糊多属性决策方法。首先,构建各决策者区间直觉模糊集评分矩阵,并根据模糊熵获得各决策者权重。其次,利用区间模糊集集成算子得到区间直觉模糊综合决策矩阵,进而选择Hamming距离表示方法,建立总离差最大化为目标的最优化模型客观确定属性权重。然后,基于得分函数的定义及性质将原始得分函数进行改进,获得各方案的得分区间矩阵,并将其与决策者属性进行综合得到综合得分区间。最后,根据区间数中心和半径的全序关系对方案的距离,计算每个方案的最终得分,并通过某公司选择投资企业算例验证该方法的可行性和有效性。 相似文献
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基于GOWA算子的直觉模糊多属性决策方法 总被引:1,自引:0,他引:1
针对直觉模糊环境下的多属性决策问题,提出了一种基于广义有序加权平均(GOWA)算子的决策方法。首先构造了直觉模糊集相对隶属度和相对非隶属度计算公式,使得决策方案的定性、定量指标的属性评价值和权重都可以用直觉模糊集进行统一描述,然后提出能集结直觉模糊集的GOWA算子,进而建立了直觉模糊多属性决策问题的GOWA决策方法。最后利用一个实例对文中模型与方法进行了验证、说明。 相似文献
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基于直觉模糊熵权和CC-OWA算子的雷达目标识别模型 总被引:1,自引:0,他引:1
为更完整的描述和表达雷达目标类型识别中的目标特征和目标类型之间的关系复杂性和知识缺乏性,通过直觉模糊关系描述,进而将目标识别特征信息转化为直觉模糊集信息.分析了基于直觉模糊集理论的雷达目标类型识别知识建模,揭示了直觉模糊信息的价值可以通过直觉模糊熵刻画,进而提出应用直觉模糊集的熵构造特征直觉模糊信息的权重(直觉模糊熵权),充分利用了目标类型识别知识中隐含的权重信息,并结合CC-OWA算子建立雷达目标类型识别模型与识别步骤,利用一个雷达目标识别实例说明了模型的有效性. 相似文献
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Determining the attribute weights, in the multiple attribute group decision-making analysis with interval-valued intuitionistic fuzzy information, plays a crucial role because of its direct effect on the optimal alternative. In this paper, we develop a new attribute weight based on the support and entropy measure of attribute values. Then, the interval-valued intuitionistic fuzzy combined weighted averaging (IVIFCWA) operator is proposed and its some primary properties are discussed. The IVIFCWA operator’s attribute values take the form of interval-valued intuitionistic fuzzy numbers and the principal component of the interval-valued intuitionistic fuzzy number is fully taken into account. Finally, a numerical example concerning the investment strategy is given to illustrate the validity and applicability of the proposed method. 相似文献
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提出了一种考虑决策者风险偏好且属性权重信息不完全的区间直觉模糊数多属性群决策方法。同时考虑相似度和接近度,确定每一属性的决策者权重。为了考虑决策者风险偏好对决策结果的影响和避免区间直觉模糊矩阵的渐进性,引入了决策者风险偏好系数,将集结后的综合决策矩阵转换成区间数矩阵。然后,为了客观地求出属性权重信息不完全环境下属性的权重,构建了基于区间直觉模糊交叉熵的属性权重目标规划模型,该模型不仅考虑了评价值的偏差,也强调了评价值自身的可信度。最后,通过研发项目选择问题的实例分析说明了所提方法的合理性和优越性。 相似文献
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Dong Gun Park Young Chel Kwun Jin Han Park Il Young Park 《Mathematical and Computer Modelling》2009,50(9-10):1279-1293
In this paper, we investigate the group decision making problems in which all the information provided by the decision-makers is presented as interval-valued intuitionistic fuzzy decision matrices where each of the elements is characterized by interval-valued intuitionistic fuzzy number (IVIFN), and the information about attribute weights is partially known. First, we use the interval-valued intuitionistic fuzzy hybrid geometric (IIFHG) operator to aggregate all individual interval-valued intuitionistic fuzzy decision matrices provided by the decision-makers into the collective interval-valued intuitionistic fuzzy decision matrix, and then we use the score function to calculate the score of each attribute value and construct the score matrix of the collective interval-valued intuitionistic fuzzy decision matrix. From the score matrix and the given attribute weight information, we establish an optimization model to determine the weights of attributes, and then we use the obtained attribute weights and the interval-valued intuitionistic fuzzy weighted geometric (IIFWG) operator to fuse the interval-valued intuitionistic fuzzy information in the collective interval-valued intuitionistic fuzzy decision matrix to get the overall interval-valued intuitionistic fuzzy values of alternatives, and then rank the alternatives according to the correlation coefficients between IVIFNs and select the most desirable one(s). Finally, a numerical example is used to illustrate the applicability of the proposed approach. 相似文献
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针对应急决策信息的模糊性以及大群体偏好的冲突性引起决策风险的问题,提出了一种基于模糊—冲突熵的风险性大群体应急决策方法。首先,依据决策者偏好将大群体进行聚类,得到聚集偏好矩阵;其次,提出一个直觉模糊形式的区间直觉模糊距离以减少偏好信息的丢失,同时定义广义直觉模糊数,将二者与前景理论相结合,通过转换得到聚集的直觉模糊前景决策矩阵;再次,构建以决策风险最小化为目标的大群体模糊—冲突熵应急决策模型,计算准则权重,将大群体的前景决策矩阵和准则权重相结合得到方案的综合前景值,并以此对应急方案排序;最后,通过案例的分析与对比验证了所提方法的合理性与有效性。 相似文献
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基于集对分析联系数的信息不完全直觉模糊多属性决策 总被引:2,自引:1,他引:1
信息不完全直觉模糊多属性决策是一类不确定性决策问题,其不确定性来自属性权重信息不完全和属性值的直觉模糊数表示.为了系统地刻画直觉模糊多属性决策中的不确定性,避免直觉模糊多属性决策中利用得分函数做决策的片面性和不准确性,可以将信息不完全的权重和直觉模糊数表示的属性值转化成集对分析理论中的联系数,并建立信息不完全直觉模糊多属性决策模型,通过对不确定性进行分析后作出决策.实例应用表明该决策方法具有合理性和可行性. 相似文献
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Multi-person multi-attribute decision making models under intuitionistic fuzzy environment 总被引:1,自引:0,他引:1
Zeshui Xu 《Fuzzy Optimization and Decision Making》2007,6(3):221-236
Intuitionistic fuzzy numbers, each of which is characterized by the degree of membership and the degree of non-membership
of an element, are a very useful means to depict the decision information in the process of decision making. In this article,
we investigate the group decision making problems in which all the information provided by the decision makers is expressed
as intuitionistic fuzzy decision matrices where each of the elements is characterized by intuitionistic fuzzy number, and
the information about attribute weights is partially known, which may be constructed by various forms. We first use the intuitionistic
fuzzy hybrid geometric (IFHG) operator to aggregate all individual intuitionistic fuzzy decision matrices provided by the
decision makers into the collective intuitionistic fuzzy decision matrix, then we utilize the score function to calculate
the score of each attribute value and construct the score matrix of the collective intuitionistic fuzzy decision matrix. Based
on the score matrix and the given attribute weight information, we establish some optimization models to determine the weights
of attributes. Furthermore, we utilize the obtained attribute weights and the intuitionistic fuzzy weighted geometric (IFWG)
operator to fuse the intuitionistic fuzzy information in the collective intuitionistic fuzzy decision matrix to get the overall
intuitionistic fuzzy values of alternatives by which the ranking of all the given alternatives can be found. Finally, we give
an illustrative example. 相似文献
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TOPSIS is one of the well-known methods for multiple attribute decision making (MADM). In this paper, we extend the TOPSIS method to solve multiple attribute group decision making (MAGDM) problems in interval-valued intuitionistic fuzzy environment in which all the preference information provided by the decision-makers is presented as interval-valued intuitionistic fuzzy decision matrices where each of the elements is characterized by interval-valued intuitionistic fuzzy number (IVIFNs), and the information about attribute weights is partially known. First, we use the interval-valued intuitionistic fuzzy hybrid geometric (IIFHG) operator to aggregate all individual interval-valued intuitionistic fuzzy decision matrices provided by the decision-makers into the collective interval-valued intuitionistic fuzzy decision matrix, and then we use the score function to calculate the score of each attribute value and construct the score matrix of the collective interval-valued intuitionistic fuzzy decision matrix. From the score matrix and the given attribute weight information, we establish an optimization model to determine the weights of attributes, and construct the weighted collective interval-valued intuitionistic fuzzy decision matrix, and then determine the interval-valued intuitionistic positive-ideal solution and interval-valued intuitionistic negative-ideal solution. Based on different distance definitions, we calculate the relative closeness of each alternative to the interval-valued intuitionistic positive-ideal solution and rank the alternatives according to the relative closeness to the interval-valued intuitionistic positive-ideal solution and select the most desirable one(s). Finally, an example is used to illustrate the applicability of the proposed approach. 相似文献
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The aim of this paper is to extend the VIKOR method for multiple attribute group decision making in interval-valued intuitionistic
fuzzy environment, in which all the preference information provided by the decision-makers is presented as interval-valued
intuitionistic fuzzy decision matrices where each of the elements is characterized by interval-valued intuitionistic fuzzy
number, and the information about attribute weights is partially known, which is an important research field in decision science
and operation research. First, we use the interval-valued intuitionistic fuzzy hybrid geometric operator to aggregate all
individual interval-valued intuitionistic fuzzy decision matrices provided by the decision-makers into the collective interval-valued
intuitionistic fuzzy decision matrix, and then we use the score function to calculate the score of each attribute value and
construct the score matrix of the collective interval-valued intuitionistic fuzzy decision matrix. From the score matrix and
the given attribute weight information, we establish an optimization model to determine the weights of attributes, and then
determine the interval-valued intuitionistic positive-ideal solution and interval-valued intuitionistic negative-ideal solution.
We use the different distances to calculate the particular measure of closeness of each alternative to the interval-valued
intuitionistic positive-ideal solution. According to values of the particular measure, we rank the alternatives and then select
the most desirable one(s). Finally, a numerical example is used to illustrate the applicability of the proposed approach. 相似文献