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In this paper, the study of the evolution of approximation space theory and its applications is considered in the context of rough sets introduced by Zdziss law Pawlak and information granulation as well as computing with words formulated by Lotfi Zadeh. Central to this evolution is the rough-mereological approach to approximation of information granules.(More)
This paper introduces an approach to behavioral pattern identification as a part of a study of temporal patterns in complex dynam-ical systems. Rough set theory introduced by Zdziss law Pawlak during the early 1980s provides the foundation for the construction of classifiers relative to what are known as temporal pattern tables. It is quite remarkable that(More)
This paper presents a review of the current literature on rough-set- and near-set-based approaches to solving various problems in medical imaging such as medical image segmentation, object extraction, and image classification. Rough set frameworks hybridized with other computational intelligence technologies that include neural networks, particle swarm(More)