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中文摘要：
多粒度是近年来粗糙集领域研究的一个热点方向,而粒度约简是其中的一个核心问题。为了使得多粒度粗糙集能够用于处理连续型数据,引入模糊概念,构建了基于模糊等价关系的悲观多粒度模糊粗糙集模型,并进一步给出了粒度重要度的度量方法,设计一种基于启发式的粒度约简算法。以UCI（University of California Irvine）中3组数据集进行分析,实验结果表明所设计的算法能够在保持分类准确率不发生较大变化的情况下约去冗余的粒结构。
英文摘要：
Multigranulation is one of the hot directions in rough set theory, while granulation reduction is a key prob lem in multigranulation rough set. To deal with the continuous data with multigranulation rough set, the fuzzy concept is employed and the pessimistic multigranulation fuzzy rough set is constructed based on fuzzy equivalence relation. Moreo- ver, the measurement of granulation significance is presented and a granulation reduction algorithm is designed with heu- ristic idea. Finally, the algorithm is tested on three UCI（University of California Irvine）data sets, the experimental re- suits show that the proposed algorithm can reduce redundant granulation struc hout the great changing of accura- cy of classification.
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