Unsupervised Optimal Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Introduction: Geographic Information Systems in Public Health and Medicine
Journal of Medical Systems
The extended fuzzy C-means algorithm for hotspots in spatio-temporal GIS
Expert Systems with Applications: An International Journal
Clustering algorithms based on volume criteria
IEEE Transactions on Fuzzy Systems
Fuzzy clustering with volume prototypes and adaptive cluster merging
IEEE Transactions on Fuzzy Systems
Hotspots detection in spatial analysis via the extended gustafson-kessel algorithm
Advances in Fuzzy Systems - Special issue on Fuzzy Methods and Approximate Reasoning in Geographical Information Systems
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This paper presents a spatiotemporal analysis of hotspot areas based on the Extended Fuzzy C-Means method implemented in a geographic information system. This method has been adapted for detecting spatial areas with high concentrations of events and tested to study their temporal evolution. The data consist of georeferenced patterns corresponding to the residence of patients in the district of Naples (Italy) to whom a surgical intervention to the oto-laryngopharyngeal apparatus was carried out between the years 2008 and 2012.