Machine learningGranular computing
粒计算(信息粒化)
粒计算是一种问题解决方法,它处理信息时不是在个体数据点层面,而是在“粒度”——即因不可辨别性、相似性或功能性而聚集在一起的对象的集合——上进行。它由 Lotfi Zadeh 于 1997 年提出,最初称为模糊信息粒化,后来发展成为一个广泛的框架,为模糊集、粗糙集和区间方法提供了一个统一的伞盖,使分析能够迁移到问题实际需要的任何细节层次。
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来源
- 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
如何引用本页
ScholarGate. (2026, June 2). Granular Computing (Information Granulation). ScholarGate. https://scholargate.app/zh/soft-computing/granular-computing
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