FL-GrCCA: a granular computing classification algorithm based on fuzzy lattices

DOI10.1016/J.CAMWA.2010.10.040zbMath1207.68389OpenAlexW2017271962MaRDI QIDQ630737

Zhixiang Fang, Hongbing Liu, ShengWu Xiong

Publication date: 19 March 2011

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.camwa.2010.10.040

zbMATH Keywords

granular computingfuzzy latticeinclusion measuregranulepositive valuation function

Mathematics Subject Classification ID

Reasoning under uncertainty in the context of artificial intelligence (68T37) Generalizations of lattices (06B75)

Related Items (4)

Binary image 2D shape learning and recognition based on lattice-computing (LC) techniques ⋮ The Kosko subsethood fuzzy associative memory (KS-FAM): mathematical background and applications in computer vision ⋮ Fuzzy lattice reasoning for pattern classification using a new positive valuation function ⋮ FL-GrCCA

Uses Software

• Fuzzy ARTMAP

Cites Work

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• A general framework for fuzzy morphological associative memories
• Fuzzy lattice reasoning (FLR) classifier and its application for ambient ozone estimation
• Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic
• Towards a unified modeling and knowledge-representation based on lattice theory. Computational intelligence and soft computing applications
• Information granulation and rough set approximation
• Fuzzy sets

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