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Multi-adjoint intuitionistic fuzzy rough sets

机译:多伴随直觉模糊粗糙集

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The combination of fuzzy information systems (ISs) and multi-adjoint theory has become a hot issue in the study and applications of artificial intelligence. An intuitionistic fuzzy set has more flexible and practical ability to represent information and is better in dealing with ambiguity and uncertainty when compared with the fuzzy set. Multi- adjoint intuitionistic fuzzy rough sets are constructed by using adjoint triples under intuitionistic fuzzy IS. For this purpose, the authors propose intuitionistic fuzzy indiscernibility relation and multi-adjoint approximation operators. The basic results in the multi-adjoint fuzzy rough set model are generalised to multi-adjoint intuitionistic fuzzy rough set model. The analogous results are also verified. After that, a novel approach of attribute reduction is proposed. First, a kind of approximate reduction to keep the dependence of the positive region to a degree ?± is formulated. Second, they propose a heuristic algorithm to compute the attribute reduction. At last, they employ an example to describe the processing of the algorithm.
机译:模糊信息系统(ISs)和多伴随理论的结合已经成为人工智能研究和应用中的热点问题。与模糊集相比,直觉模糊集具有更灵活,更实用的信息表示能力,并且在处理歧义和不确定性方面更好。在直觉模糊IS下,利用伴随三元组构造了多伴随直觉模糊粗糙集。为此,作者提出了直觉模糊不可分辨关系和多伴随逼近算子。将多伴随模糊粗糙集模型的基本结果推广为多伴随直觉模糊粗糙集模型。类似结果也得到了验证。之后,提出了一种新的属性约简方法。首先,制定一种近似减少以使正区域的依赖性保持在α±程度。其次,他们提出了一种启发式算法来计算属性约简。最后,他们以一个例子来描述算法的处理。

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