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Extensions of Dominance-Based Rough Set Approach in Incomplete Information System

机译:不完备信息系统中基于优势的粗糙集方法的扩展

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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.
机译:作为经典粗糙集方法的有用扩展之一,基于优势的粗糙集方法已成功应用于多准则决策问题。然而,传统的基于优势的粗糙集方法仅适用于条件属性,与分类分析成正相关。为了解决这个问题,我们提出了一种假设条件属性的扩展方法,该方法基于不完全信息系统中的基于优势的粗糙集方法,该条件属性与分类分析不仅正相关,而且负相关。此外,通过考虑不完整信息系统中未知值的存在,我们提出了有价支配关系的概念,该关系表明对象相对于条件属性支配另一个对象的可能性。通过使用值优势关系,还研究了基于模糊优势的粗糙集模型。数值示例可用来证实概念性论证。

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