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Solving the optimal location problem in forest fire control with fuzzy data points


Rojas-Mora, J and Aryal, J and Ellerkamp, P and Mangiavillano, A, Solving the optimal location problem in forest fire control with fuzzy data points, Proceedings of the AGILE'2012 International Conference on Geographic Information Science, April 24-27, Avignon, France, pp. 187-192. ISBN 978-90-816960-0-5 (2012) [Refereed Conference Paper]

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Copyright 2012 Springer-Verlag

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In this paper, we present a methodology to solve location problems when the data used is inherently fuzzy. This method, from data clusterized with the fuzzy c��means algorithm, calculates bi-dimensional fuzzy numbers from the clusters which are used to calculate a fuzzy solution. We apply the methodology, with different objective functions, to a particularly apt data set of forest fire breakouts in the Bouches du Rhone region of southern France, gathered from 1981 to 2009. The robustness of the method is then evaluated with a Monte Carlo simulation in which the number of clusters change. The solution provided with this fuzzy method provides leeway to planners, which can see how the membership function of the fuzzy solution can be used as a measurement of "appropriateness" of the final location.

Item Details

Item Type:Refereed Conference Paper
Research Division:Environmental Sciences
Research Group:Environmental management
Research Field:Environmental management
Objective Division:Environmental Management
Objective Group:Terrestrial systems and management
Objective Field:Terrestrial biodiversity
UTAS Author:Aryal, J (Dr Jagannath Aryal)
ID Code:80476
Year Published:2012
Deposited By:Geography and Environmental Studies
Deposited On:2012-11-01
Last Modified:2017-11-01

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