Abstract
Problem-solving in situations of uncertainty is a key issue in achieving effective computational systems. Various techniques have been developed to address uncertainty, including Soft Computing, which has established itself as an area of significant interest. On the other hand, rough sets theory has become an effective means of dealing with uncertainty, particularly when it arises as a result of inconsistencies in the data. The present paper surveys an analysis of the relationship between rough sets and other components of Soft Computing, and of how this hybridization helps improve system performance.
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