Multi-level interval-valued fuzzy concept lattices and their attribute reduction

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• 作者：Lifeng Li
• 关键词：Interval ; valued fuzzy formal context ; Multi ; level interval ; valued concept lattice ; Attribute reduction
• 刊名：International Journal of Machine Learning and Cybernetics
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：8
• 期：1
• 页码：45-56
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Computational Intelligence; Artificial Intelligence (incl. Robotics); Control, Robotics, Mechatronics; Complex Systems; Systems Biology; Pattern Recognition;
• 出版者：Springer Berlin Heidelberg
• ISSN：1868-808X
• 卷排序：8

文摘

The paper introduces the multi-level interval-valued fuzzy concept lattices in an interval-valued fuzzy formal context. It introduces the notion of multi-level attribute reductions in an interval-valued fuzzy formal context and investigates related properties. In addition, the paper formulates a corresponding attribute reduction method by constructing a discernibility matrix and its associated Boolean function. The paper also proposes the multi-level granule representation in interval-valued fuzzy formal contexts.