A computational pipeline for modeling and predicting wildfire behavior

dc.contributor.authorFachada, Nuno
dc.contributor.institutionFaculdade de Engenharia
dc.date.issued2022-04-24
dc.descriptionCOMPLEXIS 2022 - 7th International Conference on Complexity, Future Information Systems and Risk
dc.description.abstractWildfires constitute a major socioeconomic burden. While a number of scientific and technological methods have been used for predicting and mitigating wildfires, this is still an open problem. In turn, agent-based modeling is a modeling approach where each entity of the system being modeled is represented as an independent decision-making agent. It is a useful technique for studying systems that can be modeled in terms of interactions between individual components. Consequently, it is an interesting methodology for modeling wildfire behavior. In this position paper, we propose a complete computational pipeline for modeling and predicting wildfire behavior by leveraging agent-based modeling, among other techniques. This project is to be developed in collaboration with scientific and civil stakeholders, and should produce an open decision support system easily extendable by stakeholders and other interested parties. Keywords: Agent-based Modeling, High-performance Computing, Computational Intelligence, Verification and Validation, Wildfires.pt
dc.description.statusNon peer reviewed
dc.formatapplication/pdf
dc.identifier.citationFachada , N 2022 , ' A computational pipeline for modeling and predicting wildfire behavior ' , Paper presented at SciTePress , 24/04/22 .
dc.language.isoeng
dc.publisherSciTePress
dc.rightsopenAccess
dc.subjectINFORMÁTICA
dc.subjectCOMPUTAÇÃO
dc.subjectCOMPUTAÇÃO DE ALTO DESEMPENHO
dc.subjectMODELAÇÃO BASEADA EM AGENTES
dc.subjectINCÊNDIOS
dc.subjectCOMPUTER SCIENCE
dc.subjectCOMPUTATION
dc.subjectHIGH-PERFORMANCE COMPUTING
dc.subjectAGENT-BASED MODELING
dc.subjectFIRES
dc.titleA computational pipeline for modeling and predicting wildfire behavioren
dc.typeconferenceObject

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