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论文类型：期刊论文

发表时间：2008-08-01

发表刊物：JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION

收录刊物：SCIE、Scopus

卷号：4

期号：3

页面范围：581-609

ISSN号：1547-5816

摘要：In this paper we will propose a new classifier design based on the AFS fuzzy theory. First, we will briefly review the current researches in data classification based on fuzzy and rough set theories and then present the AFS framework. Second, we will present new membership functions for fuzzy sets with their logic operations in the AFS framework and then tackle some theoretical and computational problems related to classifier design. Third, we will develop a new approach for fuzzy classifier design based on the proposed membership functions and their logic operations. Finally, a well-known example is used to illustrate its effectiveness. The advantage of this classifier is in two-folds. One is that it can mimic the human reasoning comprehensively and offers a far more flexible and effective way for the study of large-scale intelligent systems. The other is its simplicity in methodology and mathematical beauty in fuzzy theory.