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This document reviews the advancements in wildfire behavior prediction, highlighting the evolution from empirical to physical and data-driven models. It emphasizes the integration of multidisciplinary techniques, such as machine learning, to improve prediction accuracy and robustness. The authors advocate for the development of intelligent forecasting systems that utilize diverse data sources to enhance proactive fire management strategies, ultimately supporting ecological conservation and sustainable devel

Author

kimcholho24

Language

EN