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AI could transform catastrophe modelling of secondary perils

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Título: AI could transform catastrophe modelling of secondary perils / Joshua GeerAutor: Geer, Joshua
Notas: Sumario: Artificial intelligence (AI) and machine learning (ML) are poised to significantly enhance catastrophe modelling for secondary perils, such as severe convective storms, derechos, tornadoes, and wildfires, by leveraging vast amounts of high-resolution atmospheric data. Karen Clark, founder of Karen Clark & Company, emphasized during the Rendez-Vous de Septembre in Monte Carlo that AI and ML can improve forecasting accuracy for events traditionally difficult to predict, like derechos and tornado touchdowns, and can also help model wildfire behavior by analyzing wind patterns that influence fire spreadRegistros relacionados: En: Insurance ERM: the online resource for enterprise risk management. - 16 September 2025 ; 1 p.Materia / lugar / evento: Catástrofes naturales Inteligencia artificial Seguro de riesgos extraordinarios Machine learning Modelos predictivos Riesgos meteorológicos Incendios Outras classificações: 328.1
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