MULTI TASK LEARNING WITH INCOMPLETE LABELS FOR PREDICTIVE MAINTENANCE

    公开(公告)号:US20210048809A1

    公开(公告)日:2021-02-18

    申请号:US16540810

    申请日:2019-08-14

    Applicant: Hitachi, Ltd.

    Abstract: Example implementations described herein involve, for data having incomplete labeling to generate a plurality of predictive maintenance models, processing the data through a multi-task learning (MTL) architecture including generic layers and task specific layers for the plurality of predictive maintenance models configured to conduct tasks to determine outcomes for one or more components associated with the data, each task specific layer corresponding to one of the plurality of predictive maintenance models; the generic layers configured to provide, to the task specific layers, associated data to construct each of the plurality of predictive maintenance models; and executing the predictive maintenance models on subsequently recorded data.

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