A novel interval-valued data driven type-2 possibilistic local information c-means clustering for land cover classification

DOI10.1016/J.IJAR.2022.05.007OpenAlexW4281961926MaRDI QIDQ2169187

Xiaokang Guo, Chengmao Wu

Publication date: 2 September 2022

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ijar.2022.05.007

zbMATH Keywords

interval-valued datainterval type-2 fuzzy setlocal informationland cover classificationpossibilistic C-means clustering

Mathematics Subject Classification ID

Reasoning under uncertainty in the context of artificial intelligence (68T37)

Related Items (2)

Interval type-2 possibilistic fuzzy clustering noisy image segmentation algorithm with adaptive spatial constraints and local feature weighting \& clustering weighting ⋮ Improved interval type-2 fuzzy K-means clustering based on adaptive iterative center with new defuzzification method

Uses Software

• Apache Spark

Cites Work

• L\({}_ 1\)-norm based fuzzy clustering
• Fuzzy sets as a basis for a theory of possibility
• Comparison of fuzzy numbers using a fuzzy distance measure
• Suppressed robust picture fuzzy clustering for image segmentation
• Xie-Beni-Type Fuzzy Cluster Validation in Fuzzy Co-clustering of Documents and Keywords
• The Kappa Statistic: A Second Look
• Suppressed fuzzy c-means clustering algorithm

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