Combining forecasts of varying spatial and temporal resolution

A method of generating an aggregate forecast includes obtaining historical forecasts for a number of time steps and at least one location, obtaining historical conditions for the time steps and the at least one location, training a machine learning algorithm to produce an aggregate historical foreca...

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Bibliographic Details
Main Authors Lu, Siyuan, Izumiyama, Taku, Schmude, Johannes W, Hasegawa, Masao, Hamann, Hendrik F, Sakurai, Akihisa
Format Patent
LanguageEnglish
Published 21.06.2022
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
MEASURING
METEOROLOGY
PHYSICS
TESTING
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Summary:A method of generating an aggregate forecast includes obtaining historical forecasts for a number of time steps and at least one location, obtaining historical conditions for the time steps and the at least one location, training a machine learning algorithm to produce an aggregate historical forecast in response to the historical conditions and the historical forecasts, and producing an aggregate current forecast by running the trained machine learning algorithm on current forecasts. The historical forecasts and the current forecasts vary in at least one of spatial resolution or temporal resolution, and include a first forecast that is valid for a first time step and a second forecast that is valid for a second time step.
Bibliography:Application Number: US201916729408