TY - GEN
T1 - A computational pipeline for modeling and predicting wildfire behavior
AU - Fachada, Nuno
N1 - Copyright © 2022 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.
PY - 2022
Y1 - 2022
N2 - Wildfires 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.
AB - Wildfires 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.
KW - INFORMÁTICA
KW - COMPUTAÇÃO
KW - COMPUTAÇÃO DE ALTO DESEMPENHO
KW - MODELAÇÃO BASEADA EM AGENTES
KW - INCÊNDIOS
KW - COMPUTER SCIENCE
KW - COMPUTATION
KW - HIGH-PERFORMANCE COMPUTING
KW - AGENT-BASED MODELING
KW - FIRES
UR - http://hdl.handle.net/10437/12850
UR - http://www.scopus.com/inward/record.url?scp=85150481808&partnerID=8YFLogxK
U2 - 10.5220/0011073900003197
DO - 10.5220/0011073900003197
M3 - Conference contribution
T3 - International Conference on Complexity, Future Information Systems and Risk, COMPLEXIS - Proceedings
SP - 79
EP - 84
BT - COMPLEXIS 2022 - Proceedings of the 7th International Conference on Complexity, Future Information Systems and Risk
A2 - Xie, Min
A2 - Behringer, Reinhold
A2 - Chang, Victor
PB - Science and Technology Publications, Lda
T2 - 7th International Conference on Complexity, Future Information Systems and Risk, COMPLEXIS 2022
Y2 - 23 April 2022 through 24 April 2022
ER -