The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 03, 2024

Filed:

Sep. 26, 2019
Applicant:

Sofar Ocean Technologies, Inc., San Francisco, CA (US);

Inventors:

Evan Shapiro, San Francisco, CA (US);

Tim Janssen, Montara, CA (US);

Pieter Smit, Stanford, CA (US);

Assignee:

Sofar Ocean Technologies, Inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G01W 1/10 (2006.01); G01W 1/00 (2006.01); G01W 1/18 (2006.01); G06F 11/00 (2006.01); G06N 3/02 (2006.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01); G06N 3/088 (2023.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G01W 1/10 (2013.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G01W 1/00 (2013.01); G01W 2001/006 (2013.01); G01W 1/18 (2013.01); G01W 2203/00 (2013.01); G06F 11/00 (2013.01); G06N 3/02 (2013.01); G06N 3/044 (2023.01); G06N 3/088 (2013.01); G06N 20/00 (2019.01); Y02A 90/10 (2018.01);
Abstract

A computer-implemented method for forecasting weather uses a trained machine learning model to determine the error in a weather forecast, e.g., for a selected ocean region. The machine learning model is configured to determine the predicted forecasting error given the weather forecast and a set of existing conditions. The weather forecast is adjusted using the predicted forecasting error to produce an augmented weather forecast. Training the machine learning model may include the utilization of hindcasting methods. Determination of existing conditions and other modeling may include the use of data from an array of metocean sensor nodes dispersed on a body of water.


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