Covering-based granular computing

Granular computing is a methodology for intelligent information processing. It uses granules such as classes, clusters, subsets, and blocks to construct an efficient computational model for complex applications with huge amounts of data, information and knowledge. This subject is related to other fields such as artificial intelligence, cluster analysis, fuzzy set theory, quotient space theory, belief functions, machine learning, but granular computing mainly adopts concepts and methods from computing with word and rough set theory. Dr. Lin first gave a formal name for this paradigm.