Extended fuzzy C-means clustering in GIS environment for hot spot events

Authors:
Ferdinando Di Martino;Vincenzo Loia;Salvatore Sessa
Affiliations:
Università degli Studi di Salerno, Dipartimento di Matematica e Informatica, Fisciano, Salerno, Italy;Università degli Studi di Salerno, Dipartimento di Matematica e Informatica, Fisciano, Salerno, Italy;Università degli Studi di Napoli Federico II, Dipartimento di Costruzioni e Metodi Matematici in Architettura, Napoli, Italy
Venue:
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
Year:
2007

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Abstract

The Extended Fuzzy C-Means (EFCM) algorithm in a Geographic Information System (GIS) is used for identifying the volume clusters as Hot Spot areas, being the data events geo-referenced as points on the geographic map. We have implemented EFCM with the usage of the software tools ESRI/ARCGIS and ESRI/ARCVIEW 3.x and moreover we have made a comparison with the classical Fuzzy C-Means (FCM) algorithm. The application concerns a specific problem of maintenance, executed in the years 2001-2005, over the buildings constructed before 1960 in the city of Cava de' Tirreni, located in the district of Salerno (Italy).