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).
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© 2007 Springer-Verlag Berlin Heidelberg
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Di Martino, F., Loia, V., Sessa, S. (2007). Extended Fuzzy C-Means Clustering in GIS Environment for Hot Spot Events. In: Apolloni, B., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2007. Lecture Notes in Computer Science(), vol 4692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74819-9_13
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DOI: https://doi.org/10.1007/978-3-540-74819-9_13
Publisher Name: Springer, Berlin, Heidelberg
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