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Granular Computing Granular computing is a general computation theory for using granules
such as subsets, classes, objects, clusters, and elements of a universe to build an efficient …

Abstract Dominance-based Rough Set Approach (DRSA) has been proposed by the authors
to handle background knowledge about ordinal evaluations of objects from a universe, and …

The role of machine learning is to generalize from a data sample. In order to generalize,
every learning algorithm must be biased. Experience indicates that when this bias comes …

Rough set theory [1, 2] relies on the idea that some knowledge (data, information) is
available about objects of a universe of discourse U. Thus, a subset of U is defined using the …

Dominance-based rough sets generalize classical indiscernibility based rough sets by
handling ordered value sets of attributes and monotonic relationships between values of …

In this article, we characterize the Dominance-based Rough Set Approach (DRSA) from the
point of view of its topological properties. Using the concept of a bitopological space, we …

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The utility of the rough set approach to multiple criteria decision support is related to the
nature of both, the input preferential information available in decision analysis, and the …

The main purpose of this paper is to provide discussion and empirical analysis of symbolic
and non-symbolic methods for project evaluation. The part after the introduction is devoted …