A new Extended Fuzzy Particle Swarm Optimization (EFPSO) algorithm is presented and used for the determination of hotspot events in spatial analysis. In previous works (Di Martino et al. in Int J Hybrid Intell Syst 4:1–14, 2007; Di Martino and Sessa in Proceedings VISUAL 2008. LNCS 5188, Springer-Verlag, Berlin, pp. 92–95, 2008; Di Martino and Sessa in Expert Systems with Applications, to appear. doi:10.1016/j.eswa.2011.03.071, 2011) we have shown that the Extended Fuzzy C-Means (EFCM) can be used in the approximation of hotspot areas where the data are events geo-referenced as points on the geographic map and EFCM gives better results with respect to the classical Fuzzy C-Means. Here we compare EFPSO and EFCM, implementing both methods in a Geographic Information System. We apply the two methods to two specific datasets for crime analysis and forest fire point-events showing that EFPSO has the best performance with respect to EFCM.

A fuzzy particle swarm optimization algorithm and its application to hotspot events in spatial analysis / Di Martino, F.; Sessa, Salvatore. - In: JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING. - ISSN 1868-5137. - 4:1(2013), pp. 85-97. [10.1007/s12652]

A fuzzy particle swarm optimization algorithm and its application to hotspot events in spatial analysis

F. Di Martino;SESSA, SALVATORE
2013

Abstract

A new Extended Fuzzy Particle Swarm Optimization (EFPSO) algorithm is presented and used for the determination of hotspot events in spatial analysis. In previous works (Di Martino et al. in Int J Hybrid Intell Syst 4:1–14, 2007; Di Martino and Sessa in Proceedings VISUAL 2008. LNCS 5188, Springer-Verlag, Berlin, pp. 92–95, 2008; Di Martino and Sessa in Expert Systems with Applications, to appear. doi:10.1016/j.eswa.2011.03.071, 2011) we have shown that the Extended Fuzzy C-Means (EFCM) can be used in the approximation of hotspot areas where the data are events geo-referenced as points on the geographic map and EFCM gives better results with respect to the classical Fuzzy C-Means. Here we compare EFPSO and EFCM, implementing both methods in a Geographic Information System. We apply the two methods to two specific datasets for crime analysis and forest fire point-events showing that EFPSO has the best performance with respect to EFCM.
2013
A fuzzy particle swarm optimization algorithm and its application to hotspot events in spatial analysis / Di Martino, F.; Sessa, Salvatore. - In: JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING. - ISSN 1868-5137. - 4:1(2013), pp. 85-97. [10.1007/s12652]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/420965
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