Increase in the quality of the prediction of a computational wildfire behavior method through the improvement of the internal metaheuristic
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- 作者：Miguel Mé ; ndez-Garabettia ; b ; c ; mmendez@itu.uncu.edu.ar" class="auth_mail" title="E-mail the corresponding author ; Germá ; n Bianchinia ; gbianchini@frm.utn.edu.ar" class="auth_mail" title="E-mail the corresponding author ; Paola Caymes-Scutaria ; b ; pcaymesscutari@frm.utn.edu.ar" class="auth_mail" title="E-mail the corresponding author ; Marí ; a Laura Tardivoa ; b ; d ; lauratardivo@dc.exa.unrc.edu.ar" class="auth_mail" title="E-mail the corresponding author
- 关键词：Wildfire behavior prediction ; Simulation ; Uncertainty reduction ; Parallel Evolutionary Algorithms ; Statistical System
- 刊名：Fire Safety Journal
- 出版年：2016
- 出版时间：May 2016
- 年：2016
- 卷：82
- 期：Complete
- 页码：49-62
- 全文大小：2491 K
文摘
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ESS-IM is an uncertainty reduction method applied to wildfire spread prediction.
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ESS-IM is based on Fire Simulation, HPC and Parallel Evolutionary Algorithms.
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ESS-IM has been validated using a set of real burns.
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ESS-IM uses multiple overlapping solutions which benefits the fire prediction.
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ESS-IM increases the quality of the prediction by incorporating the Island Model.