Title:
PREDICTION AND OPERATIONAL EFFICIENCY FOR SYSTEM-WIDE OPTIMIZATION OF AN INDUSTRIAL PROCESSING SYSTEM
Document Type and Number:
WIPO Patent Application WO/2023/173987
Kind Code:
A1
Abstract:
A relationship between an input, a set-point of a plurality of processes and an output of a corresponding process is learned using machine learning. A regression function is derived for each process based upon historical data. An autoencoder is trained for each process based upon the historical data to form a regularizer and the regression functions and regularizers are merged together into a unified optimization problem. System level optimization is performed using the regression functions and regularizers and a set of optimal set-points of a global optimal solution for operating the processes is determined. An industrial system is operated based on the set of optimal set-points.
Inventors:
PHAN DZUNG TIEN (US)
VU LONG (US)
SUBRAMANIAN DHARMASHANKAR (US)
VU LONG (US)
SUBRAMANIAN DHARMASHANKAR (US)
Application Number:
PCT/CN2023/076184
Publication Date:
September 21, 2023
Filing Date:
February 15, 2023
Export Citation:
Assignee:
IBM (US)
IBM CHINA CO LTD (CN)
IBM CHINA CO LTD (CN)
International Classes:
G06N7/00; G06N20/00
Domestic Patent References:
| WO2021197783A1 | 2021-10-07 |
Foreign References:
| US20220027685A1 | 2022-01-27 | |||
| CN112826459A | 2021-05-25 | |||
| CN112015153A | 2020-12-01 | |||
| CN106875511A | 2017-06-20 | |||
| CN114168583A | 2022-03-11 | |||
| CN106485353A | 2017-03-08 | |||
| CN113065649A | 2021-07-02 | |||
| CN114170474A | 2022-03-11 |
Other References:
刘忠雨: "正则自编码器", 深入浅出图神经网络 GNN原理解析, 31 January 2020 (2020-01-31)
Attorney, Agent or Firm:
CCPIT PATENT AND TRADEMARK LAW OFFICE (CN)
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