Abstract
Model-driven approaches that use numerical simulations with observation data as initial input parameters have been mainly used in forecasting weather phenomena. On the other hand, in the recent AI boom, research on data-driven approaches that replace some of these approaches with machine learning has been actively conducted. In this presentation, I will discuss the integration of numerical simulation and machine learning in weather forecasting, and also introduce the activities to improve the accuracy of typhoon forecasting through holding a data analysis competition.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: The Proceedings of Mechanical Engineering Congress, Japan
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
