Machine learningGranular computing
Granular Computing (Information Granulation)
Granular computing is a problem-solving paradigm that processes information in 'granules' — clumps of objects drawn together by indistinguishability, similarity, or functionality — rather than at the level of individual data points. Articulated by Lotfi Zadeh in 1997 as fuzzy information granulation and developed into a broad framework, it provides a unifying umbrella over fuzzy sets, rough sets, and interval methods, letting analysis move to whichever level of detail a problem actually requires.
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Sources
- Zadeh, L. A. (1997). Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets and Systems, 90(2), 111–127. DOI: 10.1016/S0165-0114(97)00077-8 ↗
- Pedrycz, W., Skowron, A., & Kreinovich, V. (Eds.). (2008). Handbook of Granular Computing. Wiley. ISBN: 978-0-470-03554-2