APPLICATION OF ADAPTIVE NEURO-FUZZY INTERFERENCE SYSTEM MODELS FOR PREDICTION OF FOREST FIRES IN THE USA ON THE BASIS OF SOLAR ACTIVITY

被引：13

作者：

Radovanovic, Milan M. ^{[1
]}

Vyklyuk, Yaroslav ^{[2
]}

Milenkovic, Milan ^{[1
]}

Vukovic, Darko B. ^{[1
]}

Matsiuk, Nataliya ^{[3
]}

机构：

[1] Serbian Acad Arts & Sci, Geog Inst Jovan Cvijic, Belgrade, Serbia

[2] Bukovynian Univ, Chernovtsy, Ukraine

[3] Bukovynian State Finance & Econ Univ, Chernovtsy, Ukraine

来源：

THERMAL SCIENCE | 2015年 / 19卷 / 05期

关键词：

forest fires; heliocentric hypothesis; Hurst index; adaptive neuro-fuzzy interference system models; USA; LEVEL FLUCTUATIONS; VARIABILITY; ATMOSPHERE; ENERGY;

D O I：

10.2298/TSCI150210093R

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

In this research we search for a functional dependence between the occurrence of forest fires in the USA and the factors which characterize the solar activity. For this purpose we used several methods (R/S analysis, Hurst index) to establish potential links between the influx of some parameters from the Sun and the occurrence of forest fires with lag of several days. We found evidence for a connection and developed a prognostic scenario based on the adaptive neuro-fuzzy interference system technique. This scenario allows the prediction between 79-93% of forest fires.

引用

页码：1649 / 1661

页数：13

共 35 条

[1]

Abraham A., 2005, STUD FUZZ SOFT COMP, V181, P53, DOI 10.1007%2F11339366_3

[2] A comparison of different rule-based statistical models for modeling geogenic groundwater contamination [J].

Amini, Manouchehr ;

Abbaspour, Karim C. ;

Johnson, C. Annette .

ENVIRONMENTAL MODELLING & SOFTWARE, 2010, 25 (12) :1650-1657

[3]

[Anonymous], 1997, IEEE Trans. Autom. Control

[4]

Bell WilliamR., 2012, Economic Time series: modeling and seasonality

[5]

Boxall M., 2009, ESS GUIDELINES SEASO

[6]

Cumming SG, 2001, ECOL APPL, V11, P97, DOI 10.1890/1051-0761(2001)011[0097:FTAWIT]2.0.CO

[7]

[8] Solar Forcing of Climate [J].

de Jager, C. .

SURVEYS IN GEOPHYSICS, 2012, 33 (3-4) :445-451

[9]

Ducic V, 2008, J GEOGR INST JOVAN C, V58, P59

[10] Prediction of building energy needs in early stage of design by using ANFIS [J].

Ekici, Betul Bektas ;

Aksoy, U. Teoman .

EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (05) :5352-5358

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