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The Weighted Fuzzy Barycenter: Definition and Application to Forest Fire Control in the PACA Region

The Weighted Fuzzy Barycenter: Definition and Application to Forest Fire Control in the PACA Region

Julio Rojas-Mora, Didier Josselin, Jagannath Aryal, Adrien Mangiavillano, Philippe Ellerkamp
Copyright: © 2013 |Volume: 4 |Issue: 4 |Pages: 20
ISSN: 1947-3192|EISSN: 1947-3206|EISBN13: 9781466658936|DOI: 10.4018/ijaeis.2013100103
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MLA

Rojas-Mora, Julio, et al. "The Weighted Fuzzy Barycenter: Definition and Application to Forest Fire Control in the PACA Region." IJAEIS vol.4, no.4 2013: pp.48-67. http://doi.org/10.4018/ijaeis.2013100103

APA

Rojas-Mora, J., Josselin, D., Aryal, J., Mangiavillano, A., & Ellerkamp, P. (2013). The Weighted Fuzzy Barycenter: Definition and Application to Forest Fire Control in the PACA Region. International Journal of Agricultural and Environmental Information Systems (IJAEIS), 4(4), 48-67. http://doi.org/10.4018/ijaeis.2013100103

Chicago

Rojas-Mora, Julio, et al. "The Weighted Fuzzy Barycenter: Definition and Application to Forest Fire Control in the PACA Region," International Journal of Agricultural and Environmental Information Systems (IJAEIS) 4, no.4: 48-67. http://doi.org/10.4018/ijaeis.2013100103

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Abstract

In this paper, the authors present a methodology to solve the weighted barycenter problem when the data is inherently fuzzy. This method, from data clustered by expert visual inspection of maps, calculates bi-dimensional fuzzy numbers from the spatial clusters, which in turn are used to obtain the weighted fuzzy barycenter of a particular area. The authors apply the methodology, to a particularly apt data set of forest fire breakouts in the PACA region of southeastern France, gathered from 1986 to 2008, and sliced into five periods over which the fuzzy weighted barycenter for each one is obtained. Two weighting schemes based on fire intensity and fire density in a cluster were used. The center 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.

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