ScholarGate
助手
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。

在 MethodMind 中打开即将推出视频即将推出Download slides

阅读完整方法

仅限会员

使用免费账户登录即可阅读本节。

登录

Method map

The neighbourhood of related methods — select a node to explore.

来源

  1. 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
  2. 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

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

Compare side by side

被引用于

ScholarGateGranular Computing (Granular Computing (Information Granulation)). 于 2026-06-15 检索自 https://scholargate.app/zh/soft-computing/granular-computing · 数据集: https://doi.org/10.5281/zenodo.20539026