Tailored Warning System Based on Weather Conditions Using Neural Network Models
Monday, May 13, 2024 3:00 PM to Wednesday, May 15, 2024 4:00 PM · 2 days 1 hr. (Europe/Berlin)
Foyer D-G - 2nd floor
Project Poster
AI Applications powered by HPC TechnologiesEarth, Climate and Weather ModelingHigh-Performance Data AnalyticsHPC Simulations enhanced by Machine LearningML Systems and Tools
Information
Poster is on display.
The Tailored Warning System based on Weather Conditions using Neural Network Models addresses the critical need for accurate and timely notifications in domains affected by weather-related risks. By leveraging numerical weather prediction models and artificial intelligence techniques, this project aims to provide customized warnings and alerts to diverse stakeholders, including flood warnings, winter weather alerts, air quality notifications, cloud seeding decisions, tropical storm and hurricane tracking, drought and farmer notifications, and health warnings. To enhance the system's performance and scalability, High-Performance Computing (HPC) resources are utilized. HPC enables efficient processing and analysis of large-scale weather data, allowing for faster model training, hyperparameter optimization, and real-time predictions. By leveraging the computational power of HPC infrastructure, the system can handle complex neural network models, big datasets, and computationally intensive tasks. This empowers the system to deliver accurate and tailored warnings within tight timeframes, ensuring stakeholders have timely information to make informed decisions and take appropriate actions. The integration of HPC in the system enhances its capabilities and enables it to meet the demanding requirements of real-time weather forecasting and warning dissemination.
Contributors:
The Tailored Warning System based on Weather Conditions using Neural Network Models addresses the critical need for accurate and timely notifications in domains affected by weather-related risks. By leveraging numerical weather prediction models and artificial intelligence techniques, this project aims to provide customized warnings and alerts to diverse stakeholders, including flood warnings, winter weather alerts, air quality notifications, cloud seeding decisions, tropical storm and hurricane tracking, drought and farmer notifications, and health warnings. To enhance the system's performance and scalability, High-Performance Computing (HPC) resources are utilized. HPC enables efficient processing and analysis of large-scale weather data, allowing for faster model training, hyperparameter optimization, and real-time predictions. By leveraging the computational power of HPC infrastructure, the system can handle complex neural network models, big datasets, and computationally intensive tasks. This empowers the system to deliver accurate and tailored warnings within tight timeframes, ensuring stakeholders have timely information to make informed decisions and take appropriate actions. The integration of HPC in the system enhances its capabilities and enables it to meet the demanding requirements of real-time weather forecasting and warning dissemination.
Contributors:
Format
On-site
