Invention Application
- Patent Title: INTEGRATING MACHINE LEARNING INTO CONTROL SYSTEMS FOR INDUSTRIAL FACILITIES
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Application No.: US16654978Application Date: 2019-10-16
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Publication No.: US20200050178A1Publication Date: 2020-02-13
- Inventor: Jim Gao , Christopher Gamble , Amanda Gasparik , Vedavyas Panneershelvam , David Barker , Dustin Reishus , Abigail Ward , Jerry Luo , Brian Kim , Mark Schwabacher , Stephen Webster , Timothy Jason Kieper , Daniel Fuenffinger , Zakerey Bennett
- Applicant: Google LLC
- Main IPC: G05B19/4155
- IPC: G05B19/4155 ; G06N20/00

Abstract:
Methods, systems, apparatus and computer program products for implementing machine learning within control systems are disclosed. An industrial facility setting slate can be received from a machine learning system and a determination can be made as to whether to adopt the settings in the industrial facility setting slate. The machine learning model can be a neural network, e.g., a deep neural network, that has been trained, e.g., using reinforcement learning to predict a data setting slate that is predicted to optimize an efficiency of a data center.
Information query
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