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856 条记录 (耗时 0.026 秒)

    MACHINE LEARNING MODEL PROCESSING METHOD AND APPARATUS, AND STORAGE MEDIUM
    73.
    发明公开
    MACHINE LEARNING MODEL PROCESSING METHOD AND APPARATUS, AND STORAGE MEDIUM 审中-实审

    公开(公告)号：EP4398161A1

    公开(公告)日：2024-07-10

    申请号：EP22863627.0

    申请日：2022-09-02

    申请人： Datang Mobile Communications Equipment Co., Ltd.

    发明人： DUAN, Xiaoyan

    IPC分类号： G06N20/20 ,  H04W40/02

    CPC分类号： G06N20/00 ,  G06N20/20 ,  H04L41/082 ,  H04L41/14 ,  H04L41/16 ,  H04W16/22 ,  H04W40/02

    摘要： The present disclosure provides a machine learning model processing method and apparatus, and a storage medium. A UE creates a local machine learning model for a target application in advance according to a global machine learning model provided by a first network function entity, determines local training data related to the target application, trains the local machine learning model according to the local training data, and sends local model parameters of the trained local machine learning model to the first network function entity, so that the first network function entity updates the global machine learning model. In this way, federated learning can be realized between the UE and the first network function entity for providing the model, and the performance of sharing, transmitting and training machine learning models between the UE and the network is improved, thus meeting the rapidly developing communication services and application demands.

    ACCELERATING THE THERMOPLASTICS WELDING PROCESS USING MULTI-SOURCE MACHINE LEARNING
    78.
    发明公开
    ACCELERATING THE THERMOPLASTICS WELDING PROCESS USING MULTI-SOURCE MACHINE LEARNING 审中-公开

    公开(公告)号：EP4394527A1

    公开(公告)日：2024-07-03

    申请号：EP23206442.8

    申请日：2023-10-27

    申请人： Raytheon Technologies Corporation

    发明人： Mondal, Sudeepta ,  Sarkar, Soumalya ,  Gangloff, John Joseph ,  Zhao, Wenping ,  Xing, Lei

    IPC分类号： G05B13/02 ,  B29C65/02 ,  G06N3/045

    CPC分类号： G05B13/027 ,  B29C65/02 ,  G06N3/045 ,  G06N5/01 ,  G06N20/20 ,  G06N7/01 ,  G06N20/00

    摘要： A system having a set of instructions executable by the system for multi-source machine learning modeling framework for process property mapping of thermoplastic composite manufacturing, the set of instructions comprising: an instruction to select a surrogate machine learning model from a suite of machine learning networks; an instruction to involve uncertainty quantification associated with predictions which provide a quantified estimate of how much the machine learning model can be trusted; an instruction to provide multi-physics process model output to the machine learning model; an instruction to provide heterogeneous data sources for use by the machine learning model; an instruction to determine estimates of optimal process parameters employing budget-constrained multi-fidelity process optimization; an instruction for deployment the multi-source machine learning model in the implementation of carbon fiber reinforced thermoplastic polymer induction welding; and an instruction to perform induction welding with an optimized recipe.

    REMOTE MONITORING SYSTEM, ANOMALY DETECTION SYSTEM, REMOTE MONITORING METHOD, AND PROGRAM
    79.
    发明公开
    REMOTE MONITORING SYSTEM, ANOMALY DETECTION SYSTEM, REMOTE MONITORING METHOD, AND PROGRAM 审中-实审

    公开(公告)号：EP4393662A1

    公开(公告)日：2024-07-03

    申请号：EP22861041.6

    申请日：2022-07-27

    申请人： Panasonic Intellectual Property Corporation of America

    发明人： IIO, Kentaro ,  HIRAMOTO, Takuji ,  OBA, Tatsumi

    IPC分类号： B25J19/06 ,  G08B29/02 ,  H04M11/00 ,  H04Q9/00 ,  G06N20/00

    CPC分类号： G08B29/02 ,  G06N20/00 ,  B25J19/06 ,  H04M11/00 ,  H04Q9/00

    摘要： A remote monitoring system (101) is a remote monitoring system that detects an anomaly in a state of a monitored target (102) that operates autonomously, and the remote monitoring system (101) includes: a state obtainer (201) that obtains state information indicating a state of the monitored target (102) from the monitored target (102); an information obtainer (202a) that obtains first sensing information indicating a result of sensing of the monitored target (102) from an external information source (103a) that is provided outside the monitored target (102) and performs sensing of the monitored target (102); a state estimator (203a) that estimates a first state of the monitored target (102) based on the first sensing information; a state comparer (207) that compares the state information with estimated state information that is based on the first state; and an alert issuer (206) that notifies a monitor of the remote monitoring system (101) of an occurrence of an anomaly, based on a comparison result of the state comparer (207).