Data fusion based on fuzzy measures

Choquet integral based on fuzzy measure is a very popular data fusion approach. A major problem in applying the Choquet integral is how to determine a large number of fuzzy measures as the number of attributes increases. The λ-fuzzy measure proposed by Sugeno is a powerful method to resolve this problem. However, the modeling ability of the λ-fuzzy measure is too limited to satisfy actual requirements. In this paper, an extended λ-fuzzy measure is proposed using Shapley value index, and the limitation of the λ-fuzzy measure is significantly overcome under little additional computational loads. The extended fuzzy measure has stronger modeling power than the λ-fuzzy measure, straightforwardly representing interaction among attributes. We apply the extended fuzzy measure to an artificial data set and a real dataset in an iron-steel plant. The results verify the usefulness of the extended fuzzy measure compared with other main existing methods.     

Data fusion based on fuzzy measures

Choquet integral based on fuzzy measure is a very popular data fusion approach.A major problem in applying the Cho- quet integral is how to determine a large number of fuzzy measures as the number of attributes increases.Theλ-fuzzy measure proposed by Sngeno is a powerful method to resolve this problem.However,the modeling ability of theλ-fuzzy measure is too limited to satisfy actual requirements.In this paper,an extendedλ-fuzzy measure is proposed using Shapley value index,and the limitation of theλ-fuzzy measure is significantly overcome under little additional computational loads.The extended fuzzy measure has stronger modeling power than theλ- fuzzy measure,straightforwardly representing interaction among attributes.We apply the extended fuzzy measure to an artificial data set and a real dataset in an iron-steel plant.The results verify the usefulness of the extended fuzzy measure compared with other main existing methods.     

基于Choquet模糊积分算子的多指标属性船型方案优选模型

船型方案排序及优选是一个多指标属性、多层次且指标属性相互关联的决策问题.考虑船型方案评价中各评价指标间存在的模糊性和相互关联性,利用模糊测度和Choquet模糊积分算子对船型方案进行优选.此方法的优点是考虑了方案各指标属性的关联关系,而且决策过程不用确定各指标属性的权重,减少了决策过程中决策者的主观臆断性,使排序结果更具客观性和科学性.计算实例说明:基于Choquet模糊积分方法建立的船舶方案优选模型正确,方法简单,结果合理,为船型方案选择提供了一种可靠的参考.     

基于Choquet积分的区间灰数多属性决策方法

针对多属性决策中属性间的关联性对决策结果的影响,提出了基于区间灰数灰度和Choquet积分的区间灰数多属性决策方法。根据区间灰数灰度的定义,证明了区间灰数的灰度是一种灰测度,由此定义了关于区间灰数灰度的离散Choquet积分并证明其性质;依据各方案的综合属性值的方差最小的原则建立多目标优化模型,确定了各属性或属性集的权重,最后利用Choquet积分对各方案的效果评价向量进行集成。通过实例说明了该方法的有效性。     

一种基于Choquet积分的不精确推理方法

模糊规则是模糊推理中的重要工具之一,它表示了模糊知识的因果关系.在一个模糊规则集中,当模糊命题间存在交互作用时,将参数权重用模糊测度取代,得到了一种基于模糊规则矩阵变换和Choquet模糊积分的模糊推理方法.该方法主要应用在不完全归纳推理中.     

基于一种推广的Choquet积分的回归模型

为了处理属性间带有不确定值交互作用的实际问题,提出了一种推广的Choquet积分,给出了一种基于此积分的回归模型,最后给出了用粒子群算法确定模型中回归参数的算法.由于粒子群算法具有快速收敛等优点,保证了本文提出算法的快速求解和有效性.     

λ-模糊Choquet积分的收敛性

在一般模糊测度空间上,针对给定的非负可测函数定义了λ-模糊Choquet积分,并将这种模糊积分整体看作一般模糊测度空间上的集函数,进而讨论了这种模糊积分的一些基本性质和收敛性．     

F值函数关于F测度的Choquet积分

为取值于F数的Choquet积分系列,探讨了F值函数关于F测度的Choquet积分。以区间分析为工具,在定义区间值函数Choquet积分的基础上,给出了F值函数Choquet积分的定义,得到了各种性质和收敛定理。     

具有Choquet积分形式的模糊合作对策

结合模糊数的限制运算,探讨了一类具有模糊支付的模糊合作对策--Choquet积分形式的模糊合作对策,研究了其单调性和连续性。具有模糊支付的模糊合作对策是凸模糊合作对策时,研究了Choquet积分形式的模糊合作对策的模糊核心和模糊Shapley值,并探讨了两者之间的关系,有趣的是这种关系与经典情形相一致。需要指出的是,所给有关模糊合作对策的定义都是对经典情形的推广。最后通过一个算例来说明其应用。     

基于企业综合绩效多维度评估决策分析

针对企业绩效评估在全面性方面存在的局限,提出构建N维评估系统,多角度评估影响企业绩效的关键因素,并在分析的过程中从价值、风险、成本和效益4个维度展开研究.在MACBETH绩效评估模型的基础上加入2测度Choquet积分,考虑了评估准则间的相互影响,同时降低了计算的复杂度.根据评估准则的权重和影响因子聚集得到综合绩效,增强绩效评估的全面性,帮助企业执行有效决策.