The extended fuzzy C-means algorithm for hotspots in spatio-temporal GIS

被引：30

作者：

Di Martino, Ferdinando ^{[1
]}

Sessa, Salvatore ^{[1
]}

机构：

[1] Univ Naples Federico 2, Dipartimento Costruzioni & Metodi Matemat Archite, I-80134 Naples, Italy

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2011年 / 38卷 / 09期

关键词：

EFCM; FCM; GIS; Hotspot;

D O I：

10.1016/j.eswa.2011.03.071

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In spatial analysis buffer impact areas are called hotspots and are determined by means of density clustering methods. In a previous work, we found these hotspots in the context of a Geographic Information System (GIS) by using the extended fuzzy C-means (EFCM). Here we show how the spatial distribution of the hotspots can evolve temporally and like applicational example, we present the spatial-temporal evolution in the period 2000-2006 of the fire point-events data of the Santa Fe district (NM) (downloaded from URL: www.fs.fed.us/r3/gis/sfe_gis.shtml). (C) 2011 Elsevier Ltd. All rights reserved.

引用

页码：11829 / 11836

页数：8

共 11 条

[1]

[Anonymous], Pattern Recognition with Fuzzy Objective Function Algorithms

[2]

Chainey SP, 2002, INNOVATIONS GIS, V9

[3]

Di Martino F, 2009, J UNCERTAIN SYST, V3, P298

[4]

Grubesic T. H., 2001, ANN C CMRC DALL

[5]

Harries K., 1999, GEOGRAPHIC MAPPING C

[6] Fuzzy clustering with volume prototypes and adaptive cluster merging [J].

Kaymak, U ;

Setnes, M .

IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2002, 10 (06) :705-712

[7]

Kaymak U, 1997, INTELLIGENT HYBRID S, P91, DOI DOI 10.1007/97814615619104

[8] Information diffusion-based spatio-temporal risk analysis of grassland fire disaster in northern China [J].

Liu, Xingpeng ;

Zhang, Jiquan ;

Cai, Weiying ;

Tong, Zhijun .

KNOWLEDGE-BASED SYSTEMS, 2010, 23 (01) :53-60

[9]

Martino F Di, 2007, INT J HYBRID INTELL, V4, P1

[10]

MCGUIRE PG, 1999, 3 INT CRIME GEOGRAPH

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