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

摘要

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.