A Deep Neural Network to Globally Forecast the Track and Intensity of Tropical Cyclones

Recorded PresentationRecording 11B.2: A Deep Neural Network to Globally Forecast the Track and Intensity of Tropical Cyclones Boston Convention and Exhibition Center – 156A Hammad Usmani Georgia Institute of TechnologyAtlanta, GA, USA Aadil Habibi Univ. of Central FloridaOrlando, FL, USA Daanish Habibi Univ. of Central FloridaOrlando, FL, USA Tropical cyclones are the most devastating weather…

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Hurricane Helene

The 2024 Hurricane Season: A Review of Helene’s Impact and the Power of Machine Learning in Disaster Management

Overview of the 2024 Hurricane Season As the 2024 Atlantic hurricane season approaches its conclusion, it is essential to assess the predictions made at the beginning of the season against the actual outcomes. The National Oceanic and Atmospheric Administration (NOAA) forecasted an above-normal season with an 85% probability, anticipating between 17 to 25 named storms,…

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Data Archival & Backup for Emergency Preparedness

Introduction Simulations of emergency scenarios due to powerful artificial intelligence like AGI (Artificial General Intelligence) describe increased cyberattacks that elevate the risk of cloud data infrastructure. Our experimental specialty consists of deep learning models that forecast extreme weather events such as hurricanes so offline media like M-Disc stores our data as part of our disaster…

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Tracking Hurricane Milton’s Landfall: Real-Time Global Storm Mapping 🌍

We are excited to present our interactive global storm tracking map, available at https://fluids.ai/map/. This platform is built to provide real-time tracking of global storms, including Hurricane Milton, a Category 5 storm that recently made landfall as a Category 3 storm near Florida’s west coast. Using advanced satellite imagery and data feeds, users can monitor…

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