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This is a record of a document published elsewhere, first published by the United States Patent and Trademark Office, as US-12607994-B2, on 21 April 2026. OpenTechnical did not first disclose it. The identifier, hashes and timestamps below record what this library served and when, not when the material became public. View the original.

OT-2026-000000363

Machine learning for detecting and modifying faulty controls

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Classification
Sensors, Controls & Machine Vision › Industrial Control
Original source
US-12607994-B2, the United States Patent and Trademark Office, 21 April 2026
Document SHA-256
1a64e7ed9d28df0713201f3132c72f24ca93c213de42ab1b7987bcdef0c8fbbb

Abstract

In some aspects, a computing system may use machine learning to determine whether a control is faulty or generate recommendations to make a modification to a control. may identify a portion of problematic computer code that implements the faulty control through the use of machine learning. A computing system may use machine learning to generate embeddings that map incident data and control data (e.g., computer-readable code of a control) to the same vector space. Further, a computing system may use a weighting mechanism that may be used to weight each sample used to train a machine learning model, which may allow a model to train more efficiently.

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Citation

OpenTechnical Publication OT-2026-000000363, “Machine learning for detecting and modifying faulty controls,” published September 15, 2026 at 19:02:47 UTC, https://opentechnical.org/p/OT-2026-000000363.

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This record reproduces a document published elsewhere and is provided for reference and study. Rights in the original remain with its owner. See the publication policy.