Information Sciences: an International Journal
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Information Sciences: an International Journal
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Fuzzy Sets and Systems
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Information Sciences—Informatics and Computer Science: An International Journal
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Information Sciences: an International Journal
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On generalized rough fuzzy approximation operators
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On the generalization of fuzzy rough sets
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Data & Knowledge Engineering
International Journal of Approximate Reasoning
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Alternative rule induction methods based on incremental object using rough set theory
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Applied Soft Computing
Attribute reduction: A dimension incremental strategy
Knowledge-Based Systems
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Data & Knowledge Engineering
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Information Sciences: an International Journal
Information Sciences: an International Journal
Updating attribute reduction in incomplete decision systems with the variation of attribute set
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
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Abstract: The lower and upper approximations are basic concepts in rough fuzzy set theory. The effective computation of approximations is very important for improving the performance of related algorithms. This paper proposed and proved two incremental methods for fast computing the rough fuzzy approximations, one starts from the boundary set, the other is based on the cut sets of a fuzzy set. Then some illustrative examples are conducted. Consequently, two algorithms corresponding to the two incremental methods are put forward respectively. In order to test the efficiency of algorithms, some experiments are made on a large soybean data set from UCI. The experimental results show that the two incremental methods effectively reduce the computing time in comparison with the traditional non-incremental method [1].