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).
Extended Fuzzy C-Means Clustering in GIS Environment for Hot Spot Events / Sessa, Salvatore; DI MARTINO, F.; Loia, V.. - STAMPA. - 4692:(2007), pp. 101-107. (Intervento presentato al convegno KES2007/WIRN 2007 tenutosi a Vietri sul Mare, Italy nel 12-14 settembre 2007) [10.1007/978-3-540-74819-9].
Extended Fuzzy C-Means Clustering in GIS Environment for Hot Spot Events
SESSA, SALVATORE;F. DI MARTINO;
2007
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).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
