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This article provides definitions and principles of granular computing and discusses the generation and online adaptation of rule-based models from data streams. Essential notions of interval analysis and fuzzy sets are addressed from the granular computing point of view. The article also covers different types of aggregation operators which perform information fusion by gathering large volumes of dissimilar information into a more compact form. We briefly summarize the main historicaldoi:10.21528/lnlm-vol14-no2-art3 fatcat:mw4xwirbsbg3ln2fciuovvlg6u