Invention Grant
- Patent Title: Classification of operating plan data using machine learning
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Application No.: US16372970Application Date: 2019-04-02
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Publication No.: US11321376B2Publication Date: 2022-05-03
- Inventor: Sabastian Terrazas-Moreno , Stacy Janak , Dimitrios Varvarezos
- Applicant: Aspen Technology, Inc.
- Applicant Address: US MA Bedford
- Assignee: Aspen Technology, Inc.
- Current Assignee: Aspen Technology, Inc.
- Current Assignee Address: US MA Bedford
- Agency: Hamilton, Brook, Smith & Reynolds, P.C.
- Main IPC: G06F16/35
- IPC: G06F16/35

Abstract:
A computer system provides improved classification of operating and scheduling plan data of a process plant. The system finds patterns in cases of the plan data and, based on the patterns, organizes the cases into a hierarchical structure of clusters representing distinct conditions. The system receives a dataset of cases of operating plan data represented by process variables. The system reduces a number of process variables representing operating plan data in the dataset by generating principal component(s) from values of the process variables for each case. The principal component(s) are latent variables generated to capture variation in conditions across the cases. For each case, the system determines a value for each generated principal component in the dataset. Using automated clustering or machine learning techniques, the system iteratively clusters the cases into a hierarchical structure based on the respective determined value of each generated principal component. The hierarchical structure provides temporal and spatial classification indicating the distinct operating conditions across cases.
Public/Granted literature
- US20200320338A1 Classification of Operating Plan Data Using Machine Learning Public/Granted day:2020-10-08
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