Improved Prediction Methods for Wildfires Using High Performance Computing: A Comparison

机译：使用高性能计算的野火改进预测方法：比较

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摘要

Recently, dry and hot seasons have seriously increased the risk of forest fire in the Mediterranean area. Wildland simulators, used to predict fire behavior, can give erroneous forecasts due to lack of precision for certain dynamic input parameters. Developing methods to avoid such parameter problems can improve significantly the fire behavior prediction. In this paper, two methods are evaluated, involving statistical and uncertainty schemes. In each one, the number of simulations that must be carried out is enormous and it is necessary to apply high-performance computing techniques to make the methodology feasible. These techniques have been implemented in parallel schemes and tested in Linux cluster using MPI.

机译：最近，干旱和炎热的季节严重增加了地中海地区森林火灾的风险。由于对某些动态输入参数缺乏精确度，用于预测火灾行为的Wildland模拟器可能会给出错误的预测。开发避免此类参数问题的方法可以显着改善火灾行为的预测。本文对两种方法进行了评估，涉及统计和不确定性方案。在每一种方法中，必须执行的模拟数量是巨大的，并且有必要应用高性能计算技术来使方法可行。这些技术已在并行方案中实现，并在使用MPI的Linux群集中进行了测试。

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来源
《International Conference on Computational Science(ICCS 2006) pt.1; 20060528-31; Reading(GB)》|2006年|P.539-546|共8页
会议地点 Reading(GB)
作者
German Bianchini; Ana Cortes; Tomas Margalef; Emilio Luque;
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作者单位

Departament d'Informatica, E.T.S.E, Universitat Autonoma de Barcelona, 08193-Bellaterra (Barcelona) Spain;

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原文格式 PDF
正文语种 eng
中图分类计算技术、计算机技术;
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Improved Prediction Methods for Wildfires Using High Performance Computing: A Comparison

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