| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6855901 | Fuzzy Sets and Systems | 2018 | 18 Pages |
Abstract
We present a spatiotemporal clustering method, namely SEFCM, which is a generalization of the extended fuzzy C-Means (EFCM) method for detecting hotspots in spatial analysis. Each pattern is formed by three features: the geographical coordinates and the period in which a certain event is occurred. This method is applied to a spatial dataset (formed by earthquake epicenters occurred in Southern Italy since 2001 till to 2014) for prediction of the hotspots obtained in a given year. Comparisons of the prediction results are also made with the ones obtained by applying the known ST-DBSCAN algorithm.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Ferdinando Di Martino, Witold Pedrycz, Salvatore Sessa,