Abstract
By combining both vague sets and rough sets in fuzzy data processing, we propose a vague-rough set approach for extracting knowledge under uncertain environments. We compute all attribute reductions using the vague-rough lower approximation distribution, concepts of attribute reduction and the discernibility matrix in a vague decision information system (VDIS). Research results for extracting decision rules from the VDIS show the proposed approaches extend the corresponding method in classical rough set theory and provide a new avenue to uncertain vague knowledge acquisition.
Details
Original language | English |
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Pages (from-to) | 837-843 |
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Journal | Knowledge-Based Systems |
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Volume | 24 |
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Issue number | 6 |
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DOIs | |
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Publication status | Published - 3 Apr 2011 |
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