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Tính toán hạt (Tổ chức thông tin)×Xác suất không chính xác×
Lĩnh vựcTính toán mềmTính toán mềm
HọMachine learningBayesian methods
Năm ra đời19971991
Người khởi xướngLotfi A. Zadeh (information granulation); developed by Pedrycz, Skowron, YaoPeter Walley
LoạiFramework for multi-granularity information processingSet-valued probability model
Công trình gốcZadeh, 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 ↗Walley, P. (1991). Statistical Reasoning with Imprecise Probabilities. Chapman & Hall. ISBN: 978-0-412-28660-5
Tên gọi khácinformation granulation, computing with granules, three-way granular computing, tanecikli hesaplamaLower-Upper Probability, Robust Bayesian Analysis, Credal Set Theory, Belirsiz Olasılık
Liên quan33
Tóm tắtGranular 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.Imprecise probability is a generalization of standard probability theory that represents epistemic uncertainty through sets of probability measures, called credal sets, rather than a single precise distribution. Introduced systematically by Peter Walley in his 1991 monograph, the framework characterizes beliefs via lower and upper probabilities (or previsions), bracketing the range of plausible probability assignments when available information is insufficient to determine a unique measure.
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ScholarGateSo sánh phương pháp: Granular Computing · Imprecise Probability. Truy cập ngày 2026-06-18 từ https://scholargate.app/vi/compare