WAVELENGTH ALIGNMENT METHOD AND APPARATUS, AND OPTICAL NETWORK SYSTEM
    2.
    发明申请
    WAVELENGTH ALIGNMENT METHOD AND APPARATUS, AND OPTICAL NETWORK SYSTEM 审中-公开
    波长对准方法和装置,以及光网络系统

    公开(公告)号:US20160134079A1

    公开(公告)日:2016-05-12

    申请号:US14996023

    申请日:2016-01-14

    Abstract: A wavelength alignment method includes: emitting a first optical signal by using a laser; filtering the first optical signal by using a filter, and then transmitting a second optical signal; monitoring an extinction ratio of the second optical signal and an optical power of the second optical signal; and adjusting a working temperature of the laser and/or a working temperature of the filter to a target working temperature when the extinction ratio of the second optical signal exceeds an upper limit of a first extinction ratio threshold range and the optical power of the second optical signal exceeds a lower limit of a first optical power threshold range or when the extinction ratio of the second optical signal exceeds a lower limit of a first extinction ratio threshold range and the optical power of the second optical signal exceeds an upper limit of a first optical power threshold range.

    Abstract translation: 波长对准方法包括:通过使用激光发射第一光信号; 通过使用滤波器对第一光信号进行滤波,然后发送第二光信号; 监测第二光信号的消光比和第二光信号的光功率; 以及当所述第二光信号的消光比超过第一消光比阈值范围的上限和所述第二光信号的光功率时,将所述激光器的工作温度和/或所述滤波器的工作温度调整到目标工作温度 信号超过第一光功率阈值范围的下限,或者当第二光信号的消光比超过第一消光比阈值范围的下限,并且第二光信号的光功率超过第一光功率阈值范围的上限时 功率阈值范围。

    METHOD AND APPARATUS FOR PREDICTING NODE STATE

    公开(公告)号:US20230117633A1

    公开(公告)日:2023-04-20

    申请号:US17984421

    申请日:2022-11-10

    Abstract: A method for predicting a node state, including: obtaining static graphs and dynamic graphs of a plurality of nodes in a target network, where the static graphs and the dynamic graphs are all topology views; generating spatial feature data of the plurality of nodes based on the static graphs and the dynamic graphs; obtaining time feature data of the plurality of nodes; and obtaining a predicted state of a target node in a target time range based on the spatial feature data and the time feature data, where the target node is any node in the plurality of nodes. The method for predicting a node state provided in this application is applied to the field of node state prediction in a network, and uses a dynamic spatial feature in addition to a time feature and a static spatial feature. FIG. 8

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