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

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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.

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Authors and Affiliations

  1. Dipartimento di Costruzioni e Metodi Matematici in Architettura, Università degli Studi di Napoli Federico II, Via Monteoliveto 3, 80134, Naples, Italy

    Ferdinando Di Martino & Salvatore Sessa

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  1. Ferdinando Di Martino
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  2. Salvatore Sessa
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Correspondence to Salvatore Sessa.

Appendix

Appendix

We report our EFPSO algorithm in the following pseudocode:

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Di Martino, F., Sessa, S. A fuzzy particle swarm optimization algorithm and its application to hotspot events in spatial analysis. J Ambient Intell Human Comput 4, 85–97 (2013). https://doi.org/10.1007/s12652-011-0096-5

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  • DOI: https://doi.org/10.1007/s12652-011-0096-5

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