Fuzzy C-modes clustering with spatial regularization and noise cluster

View Full Paper

Ask AI

Bookmark

Authors

Discussion

Analysis reveals improved clustering of urban mobility data using synthetic data, suggesting better handling of outliers.

The algorithm significantly enhances robustness in clustering categorical data, including global and local outliers.
Performance evaluations show efficacy in managing synthetic data to improve clustering outcomes.
Observational analysis applies improved fuzzy C-modes clustering to real-world data on urban mobility.
Highlights potential for better clustering techniques in urban mobility research, particularly among provincial capitals.

D'Urso et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark