公开(公告)号：US20250053885A1

公开(公告)日：2025-02-13

申请号：US18928402

申请日：2024-10-28

Applicant: ABB Schweiz AG

Inventor： Benedikt Schmidt ,  Benjamin Kloepper ,  Arzam Muzaffar Kotriwala ,  Yemao Man ,  Dawid Ziobro ,  Gayathri Gopalakrishnan ,  Joakim Astrom ,  Marcel Dix ,  Divyasheel Sharma

IPC: G06N20/20

Abstract: A method for explanation of machine learning results based on using a model collection includes training at least two machine learning models with at least two competing strategies for the at least one dataset; and using the least two machine learning models to yield at least two different predictions and/or at least two explanations for the at least one dataset.

公开(公告)号：US20250086514A1

公开(公告)日：2025-03-13

申请号：US18929807

申请日：2024-10-29

Applicant: ABB Schweiz AG

Inventor： Benjamin Kloepper ,  Dawid Ziobro ,  Divyasheel Sharma ,  Benedikt Schmidt ,  Yemao Man ,  Gayathri Gopalakrishnan ,  Joakim Astrom ,  Marcel Dix ,  Arzam Muzaffar Kotriwala

IPC: G06N20/00

Abstract: A method for deciding on a machine learning model result quality based on the identification of distractive samples in the training data includes providing a first result of the model based on initial training data; determining a first performance of the first result of the model; logging input data; providing a second result of the model based on initial training data and the input data, determining a second performance of the second result of the model and thereon based identifying erroneous data within the input data and/or the training data.

公开(公告)号：US20250117537A1

公开(公告)日：2025-04-10

申请号：US18929853

申请日：2024-10-29

Applicant: ABB Schweiz AG

Inventor： Joakim Astrom ,  Divyasheel Sharma ,  Yemao Man ,  Gayathri Gopalakrishnan ,  Benjamin Kloepper ,  Dawid Ziobro ,  Benedikt Schmidt ,  Arzam Muzaffar Kotriwala ,  Marcel Dix

IPC: G06F30/18 ,  G06F30/27 ,  G06F113/14

Abstract: A method for interactive explanations in industrial artificial intelligence systems includes providing a machine learning model and a set of test data, a set of training data and a set of historical data simulating a piping and process equipment; predicting a result for the piping and process equipment based on the machine learning model using the set of test data and the set of training data, wherein the set of historical data is used by the machine learning model to predict at least one parameter of the piping and process equipment; and presenting the predicted at least one parameter on a piping and instrumentation diagram of the piping and process equipment.

公开(公告)号：US20250053879A1

公开(公告)日：2025-02-13

申请号：US18928369

申请日：2024-10-28

Applicant: ABB Schweiz AG

Inventor： Dawid Ziobro ,  Benjamin Kloepper ,  Marcel Dix ,  Benedikt Schmidt ,  Arzam Muzaffar Kotriwala ,  Yemao Man ,  Divyasheel Sharma ,  Gayathri Gopalakrishnan ,  Joakim Astrom

IPC: G06N20/00

Abstract: A method for enabling user feedback and summarizing return of investment for machine learning systems includes providing a training data set and an initial machine learning model; providing a result of the initial machine learning model; receiving feedback on the result of the initial machine learning model from a user enriching the training dataset based on the feedback to an enriched data set; and retraining the initial machine learning model to a retrained machine learning model based on an enriched data set.