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Attribute reduction of incomplete decision table is one of the important contents of Rough Set theory. The paper presents an attribute reduction algorithm of incomplete decision table based on information entropy, where the attribute reduction method based on information entropy is studied and analyzed. In the proposed method, the relative core of decision table is treated as the starting point. And...
A new hybrid intelligent model of rough sets and RBF neural networks for fault diagnosis is proposed. Meanwhile, a novel attribute reduction approach of rough set based on artificial immune algorithm is proposed, that can find several different minimal feature set of decision table through clonal selection, mutation and antibody suppressing strategy, then provide more selection for fault diagnosis...
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