ESSIM-EA applied to Wildfire Prediction using Heterogeneous Configuration for Evolutionary Parameters

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Wildfires devastate thousands forests acres every year around the world. Fire behavior prediction is a useful tool to cooperate in the coordination, mitigation and management of available resources to fight against this type of contingencies. However, the prediction of this phenomenon is usually a d...

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Autores principales:	Méndez Garabetti, Miguel, BIanchini, Germán, Caymes Scutari, Paola, Tardivo, María Laura, Gil Costa, Graciela Verónica
Formato:	Objeto de conferencia
Lenguaje:	Inglés
Publicado:	2017
Materias:	Ciencias Informáticas Heuristic methods wildfire prediction HPC uncertainty reduction
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/63485
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-63485
record_format	dspace
institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Inglés
topic	Ciencias Informáticas Heuristic methods wildfire prediction HPC uncertainty reduction
spellingShingle	Ciencias Informáticas Heuristic methods wildfire prediction HPC uncertainty reduction Méndez Garabetti, Miguel BIanchini, Germán Caymes Scutari, Paola Tardivo, María Laura Gil Costa, Graciela Verónica ESSIM-EA applied to Wildfire Prediction using Heterogeneous Configuration for Evolutionary Parameters
topic_facet	Ciencias Informáticas Heuristic methods wildfire prediction HPC uncertainty reduction
description	Wildfires devastate thousands forests acres every year around the world. Fire behavior prediction is a useful tool to cooperate in the coordination, mitigation and management of available resources to fight against this type of contingencies. However, the prediction of this phenomenon is usually a difficult task due to the uncertainty in the prediction process. Therefore, several methods of uncertainty reduction have been developed, such as the Evolutionary Statistical System with Island Models based on Evolutionary Algorithms (ESSIM-EA). ESSIMEA focuses its operation on an Evolutionary Parallel Algorithm based on islands, in which the same configuration of evolutionary parameters is used. In this work we present an extension of the ESSIM-EA that allows each island to select an independent configuration of evolutionary parameters. The heterogeneous configuration proposed, at the island level, with the original methodology in three cases of controlled fires has been contrasted. The results show that the proposed ESSIM-EA extension allows to improve the quality of prediction and to reduce processing times.
format	Objeto de conferencia Objeto de conferencia
author	Méndez Garabetti, Miguel BIanchini, Germán Caymes Scutari, Paola Tardivo, María Laura Gil Costa, Graciela Verónica
author_facet	Méndez Garabetti, Miguel BIanchini, Germán Caymes Scutari, Paola Tardivo, María Laura Gil Costa, Graciela Verónica
author_sort	Méndez Garabetti, Miguel
title	ESSIM-EA applied to Wildfire Prediction using Heterogeneous Configuration for Evolutionary Parameters
title_short	ESSIM-EA applied to Wildfire Prediction using Heterogeneous Configuration for Evolutionary Parameters
title_full	ESSIM-EA applied to Wildfire Prediction using Heterogeneous Configuration for Evolutionary Parameters
title_fullStr	ESSIM-EA applied to Wildfire Prediction using Heterogeneous Configuration for Evolutionary Parameters
title_full_unstemmed	ESSIM-EA applied to Wildfire Prediction using Heterogeneous Configuration for Evolutionary Parameters
title_sort	essim-ea applied to wildfire prediction using heterogeneous configuration for evolutionary parameters
publishDate	2017
url	http://sedici.unlp.edu.ar/handle/10915/63485
work_keys_str_mv	AT mendezgarabettimiguel essimeaappliedtowildfirepredictionusingheterogeneousconfigurationforevolutionaryparameters AT bianchinigerman essimeaappliedtowildfirepredictionusingheterogeneousconfigurationforevolutionaryparameters AT caymesscutaripaola essimeaappliedtowildfirepredictionusingheterogeneousconfigurationforevolutionaryparameters AT tardivomarialaura essimeaappliedtowildfirepredictionusingheterogeneousconfigurationforevolutionaryparameters AT gilcostagracielaveronica essimeaappliedtowildfirepredictionusingheterogeneousconfigurationforevolutionaryparameters
bdutipo_str	Repositorios
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ESSIM-EA applied to Wildfire Prediction using Heterogeneous Configuration for Evolutionary Parameters

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