共查询到18条相似文献,搜索用时 171 毫秒
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《模式识别与人工智能》2014,(4)
传统的粗糙集理论对决策属性值为直觉模糊数的直觉模糊目标信息系统不能直接属性约简.文中在直觉模糊目标信息系统中引入优势关系,基于优势关系定义条件属性集的上近似决策协调集,给出上近似约简的判定定理,建立该信息系统条件属性集的上近似约简模型,并给出上近似约简的算法步骤.在决策属性值为直觉模糊数的一些目标信息系统中,利用条件属性集的上近似约简,可得到更为简洁的决策规则.最后给出一个实例验证算法的有效性. 相似文献
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基于优势关系的变精度粗糙集模型将传统粗糙集中的等价关系扩展为优势关系,并结合变精度的思想来定义相关概念,从而可以处理具有偏好关系的信息并具有一定的容错能力。然而,传统优势关系的定义仍然过于严格,只有当一个对象x的每个属性值都优于另一个对象y时,该对象x才优于y。当属性个数较多时,这种优势关系的定义会导致对象的优势集偏小,影响到规则的提取和决策结果。为了解决这一问题,通过引入参数的方法扩展了传统优势关系的定义,并在此基础上进一步给出了扩展后的优势集和近似集的概念,建立了扩展优势关系下的变精度粗糙集模型,采用覆盖率和测试精度作为模型的评估指标。最后给出算例,并在UCI数据集上进行大量的实验将所提模型与传统优势关系下的变精度粗糙集模型进行比较。 相似文献
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直觉模糊数据环境下的概率优势粗糙集模型是粗糙集理论的重要扩展。然而,由于实际应用数据的动态性,传统的粗糙集模型和算法面临着一定的挑战。针对该问题,提出一种直觉模糊信息系统下概率优势粗糙集的增量式更新算法。首先,利用矩阵的形式重新表达了概率优势粗糙集;然后在直觉模糊信息系统对象增加和对象减少的情形下,基于概率优势关系矩阵的增量式更新以及相关的矩阵运算,提出了直觉模糊信息系统概率优势近似集的动态更新策略;最后利用该更新策略提出了模型的增量式更新算法。实验分析结果表明,所提出的增量式更新算法具有较高的动态数据更新效率。 相似文献
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在现实生活中,许多信息系统不仅是模糊的还是基于优势关系的。在基于优势关系下模糊目标信息系统中引入了广义决策的概念,提出了分别保持下广义决策、上广义决策、广义决策不变的三种不同约简,进一步给出了各属性约简的判定定理和辨识矩阵,提供了在优势关系下模糊目标信息系统属性约简的具体方法。通过实例验证了该方法的有效性,进一步丰富了粗糙集理论。 相似文献
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利用基于优势关系的模糊粗糙集模型,讨论了模糊决策信息系统中优化序决策规则的获取问题。利用优势关系定义了模糊目标信息系统中对象的三种属性约简。给出了它们的判定定理,构造相应的区分函数,利用布尔推理技术计算对象的属性约简,得到三类新的优化序决策规则。 相似文献
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证据理论和多粒度粗糙集模型的结合已成为知识挖掘中的热点研究之一,其建立的模型已被应用于不完备、覆盖、模糊等信息系统,但在直觉模糊决策信息系统中还未见相关讨论。首先,在直觉模糊决策信息系统中利用三角模和三角余模定义了3种优势关系,得到了3种优势类,并构造了广义优势关系多粒度直觉模糊粗糙集模型;其次,基于证据理论,讨论了广义多粒度直觉模糊粗糙集的信任结构;然后,通过定义粒度重要性和属性重要性给出了属性约简方法;最后,通过实例说明了该模型在处理直觉模糊决策信息系统时是有效的。 相似文献
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置信优势关系粗糙集用于处理不完备有序决策系统,知识约简是核心问题之一。在不完备有序决策系统下区分两个对象需考虑决策值之间的偏好关系,因此给出置信优势原理关系的定义,将满足此关系的对象视为是不可区分的。提出不协调优势原理关系下的约简定义,进一步给出约简的判定定理和辨识矩阵,从而提供了在不完备有序决策系统下新的知识约简方法。通过实例验证了新的知识约简方法的有效性。 相似文献
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Lihua Wei Zhenmin Tang Runyun Wang Xibei Yang 《Automatic Control and Computer Sciences》2008,42(5):255-263
As one of the useful extensions of classical rough set approach, the dominance-based rough set approach has been successfully
applied into multi-criteria decision problems. However, the traditional dominance-based rough set approach is only suitable
for the condition attributes, which are positively related with classification analysis. To solve this problem, we propose
an extension of the dominance-based rough set approach in incomplete information system by assuming the condition attributes,
which are not only positively but also negatively related with classification analysis. Furthermore, by considering the existence
of unknown values in incomplete information system, we present the concept of valued dominance relation, which shows the probability
of an object is dominating another one with respect to the condition attributes. By using the valued dominance relation, the
fuzzy dominance-based rough set models are also studied. A numerical example is employed to substantiate the conceptual arguments.
The text was submitted in English by the authors. 相似文献
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Data mining in incomplete information systems is a hard problem but inevitable in uncertain decision. In thispaper ,an extended rough set model based on dominance relation is combined with fuzzy set theory for data mining ininterval valued decision table ,then decision rules can be obtained from the decision table. Simulation results show that the method is effective. 相似文献
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Though the dominance-based rough set approach has been applied to interval-valued information systems for knowledge discovery,
the traditional dominance relation cannot be used to describe the degree of dominance principle in terms of pairs of objects.
In this paper, a ranking method of interval-valued data is used to describe the degree of dominance in the interval-valued
information system. Therefore, the fuzzy rough technique is employed to construct the rough approximations of upward and downward
unions of decision classes, from which one can induce at least and at most decision rules with certainty factors from the interval-valued decision system. Some numerical examples are employed to substantiate
the conceptual arguments. 相似文献
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Bing Huang 《Knowledge》2011,24(7):1004-1012
Dominance interval-based fuzzy objective information systems are generalized models of single-valued fuzzy information systems. By introducing a graded dominance relation to dominance interval-valued fuzzy objective information systems, we establish a graded dominance interval-valued rough set model (RSM), which is mainly based on replacing the indiscernibility relation in classical rough set theory with the graded dominance interval-valued relation. Furthermore, in order to simplify knowledge representation and extract nontrivial simpler graded dominance interval fuzzy decision rules, we propose two attribute reduction approaches to eliminate the redundant condition attributes that are not essential from the viewpoint of graded dominance interval-valued fuzzy decision rules. These results are helpful for decision-making analysis in dominance interval-valued fuzzy objective information systems. 相似文献
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基于粗糙集的区间值属性决策表的有序规则获取 总被引:3,自引:0,他引:3
提出一种基于粗糙集的区间值属性决策表的有序规则获取方法。首先根据区间数之间基于可能度的序关系,将区间值属性决策表转化为二元决策表,然后利用粗糙集理论进行分析并推理出最优规则,最后再将二元决策表的规则转化为区间值属性决策表的有序规则。实验分析表明了该方法的有效性。 相似文献
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Fuzzy rough set is a generalization of crisp rough set, which deals with both fuzziness and vagueness in data. The measures of fuzzy rough sets aim to dig its numeral characters in order to analyze data effectively. In this paper we first develop a method to compute the cardinality of fuzzy set on a probabilistic space, and then propose a real number valued function for each approximation operator of the general fuzzy rough sets on a probabilistic space to measure its approximate accuracy. The functions of lower and upper approximation operators are natural generalizations of the belief function and plausibility function in Dempster-Shafer theory of evidence, respectively. By using these functions, accuracy measure, roughness degree, dependency function, entropy and conditional entropy of general fuzzy rough set are proposed, and the relative reduction of fuzzy decision system is also developed by using the dependency function and characterized by the conditional entropy. At last, these measure functions for approximation operators are characterized by axiomatic approaches. 相似文献
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