Patent ID: 11880015
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method comprising:
training a machine learning model, using an image-based knowledge graph of tropical cyclone data, for implementing a surface field modeling architecture that produces images of at least surface wind fields and surface rainfall fields from images of at least tropical cyclone tracks and pressure intensities;
preserving low-level features between corresponding initial convolutional layers and deep deconvolving layers of a convolutional encoder/transpose convolutional decoder via skip connections, the low-level features learned by the initial convolutional layers, and giving the deeper deconvolving layers direct access to the low-level features, the deeper deconvolving layers being layers that process data generated by at least one of the initial convolutional layers; and
generating model images of a modeled surface wind field and a modeled surface rainfall field by providing images of at least a user-generated tropical cyclone track and pressure intensity to the trained machine learning model.