We present an hotspot detection method based on the Extended Fuzzy C-Means (EFCM) algorithm for large (L) and very large (VL) datasets of events. Extensions of four VL-FCM algorithms are presented. We test our method applying these algorithms to an L dataset composed from the epicenters of earthquakes happened in Italy since 1970. Comparison have been made with respect to the results obtained by applying the EFCM algorithm on the whole event dataset and two indices are used for measuring the performances of the algorithms proposed.
Extended Fuzzy C-Means Hotspot Detection Method for Large and Very Large Event Dataset / DI MARTINO, Ferdinando; Sessa, Salvatore. - In: INFORMATION SCIENCES. - ISSN 0020-0255. - 441:(2018), pp. 198-215. [10.1016/j.ins.2018.02.029]
Extended Fuzzy C-Means Hotspot Detection Method for Large and Very Large Event Dataset
DI MARTINO, FERDINANDO;SESSA, SALVATORE
2018
Abstract
We present an hotspot detection method based on the Extended Fuzzy C-Means (EFCM) algorithm for large (L) and very large (VL) datasets of events. Extensions of four VL-FCM algorithms are presented. We test our method applying these algorithms to an L dataset composed from the epicenters of earthquakes happened in Italy since 1970. Comparison have been made with respect to the results obtained by applying the EFCM algorithm on the whole event dataset and two indices are used for measuring the performances of the algorithms proposed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
