Covering based multigranulation (I,T)-fuzzy rough set models and applications in multi-attribute group decision-making

A novel approach to information fusion in multi-source datasets

The original Pawlaks rough set approach based on indiscernibility relation (single granularity) has been extended to multigranulation rough set structure in the recent years. Multigranulation rough set approach has become a flouring research direction in rough set theory. This paper considers rough approximation of a fuzzy concept under the framework of multigranulation over two different universes of discourse, i.e., multigranulation fuzzy rough set models over two universes. We present three types of multigranulation fuzzy rough set over two universes by the constructive approach, respectively. Some interesting properties of the proposed models are discussed and also the interrelationships between the proposed models and the existing rough set models are given. We then propose a new approach to a kind of multiple criteria group decision making problem based on multigranulation fuzzy rough set model over two universes. The decision rules and algorithm of the proposed method are given and an example of handling multiple criteria group decision making problem of clothes ranking illustrates this approach. The main contribution of this paper is twofold. One is to establish the multigranulation fuzzy rough set theory over two universes. Another is to try presenting a new approach to multiple criteria group decision making based on multigranulation fuzzy rough set over two universes. The proposed models not only enrich the theory of multigranulation rough set but also make a tentative to provide a new perspective for multiple criteria group decision making with uncertainty.

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Multigranulation fuzzy rough set over two universes and its application to decision making

Regression-based three-way recommendation

Test cost sensitive multigranulation rough set: Model and minimal cost selection

Multigranulation rough set is a new and interesting topic in the theory of rough set. In this paper, the multigranulation rough sets approach is introduced into the incomplete information system. The tolerance relation, the similarity relation and the limited tolerance relations are employed to construct the optimistic and the pessimistic multigranulation rough sets, respectively. Not only the properties about these multigranulation rough sets are discussed, but also the relationships among these multigranulation rough sets models are explored. It is shown that by the multigranulation rough sets theory, the limited tolerance relations based multigranulation lower approximations fall between the tolerance and the similarity relations based multigranulation lower approximations, the limited tolerance relations based multigranulation upper approximations fall between the similarity and the tolerance relations based multigranulation upper approximations. Such results are consistent to those in single-granulation based rough sets models.

On multigranulation rough sets in incomplete information system

The neighborhood system based rough set is a generalization of Pawlak's rough set model since the former uses the neighborhood system instead of the partition for constructing target approximation. In this paper, the neighborhood system based rough set approach is employed to deal with the incomplete information system. By the coverings induced by the maximal consistent blocks and the support sets of the descriptors, respectively, two neighborhood systems based rough sets are explored. By comparing with the original maximal consistent block and descriptor based rough sets, the neighborhood system based rough sets hold the same lower approximations and the smaller upper approximations. Furthermore, the concept of attribute reduction is introduced into the neighborhood systems and the corresponding rough sets. The judgement theorems and discernibility functions to compute reducts are also presented. Some numerical examples are employed to substantiate the conceptual arguments.

Zehua Chen

Papers

On multigranulation rough sets in incomplete information system

Neighborhood system based rough set: models and attribute reductions