University of Tasmania
Browse

File(s) under permanent embargo

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

conference contribution
posted on 2023-05-23, 06:59 authored by Rojas-Mora, J, Jagannath Aryal, Ellerkamp, P, Mangiavillano, A
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.

History

Publication title

Proceedings of the AGILE'2012 International Conference on Geographic Information Science

Editors

Jérôme Gensel, Didier Josselin and Danny Vandenbroucke

Pagination

187-192

ISBN

978-90-816960-0-5

Department/School

School of Geography, Planning and Spatial Sciences

Publisher

AGILE

Place of publication

France

Event title

Proceedings of the AGILE'2012 International Conference on Geographic Information Science

Event Venue

Avignon, France

Date of Event (Start Date)

2012-04-24

Date of Event (End Date)

2012-04-27

Rights statement

Copyright 2012 Springer-Verlag

Repository Status

  • Restricted

Socio-economic Objectives

Terrestrial biodiversity

Usage metrics

    University Of Tasmania

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC