Network fault analysis method and device
A technology of network failure and analysis method, applied in the field of network maintenance, can solve the problems of low analysis efficiency and low accuracy, and achieve the effect of improving accuracy, improving efficiency and accuracy, and realizing automatic analysis.
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Embodiment 1
[0045] see figure 1 , figure 1 It is a schematic flowchart of a network fault analysis method disclosed in an embodiment of the present invention. Such as figure 1 As shown, the network failure analysis method may include the following operations:
[0046] 101. Acquire a time-series data set corresponding to a service terminal in a current fault analysis period, the time-series data set includes at least one type of time-series data, and the time-series data included in the time-series data set is used to determine the network status of the service terminal.
[0047]In an optional embodiment, the time series data in the time series data set includes the data used to represent the virtual / physical server resources occupied by the AMF in the 5G slice corresponding to the service terminal, and the data used to represent the virtual / physical server resources occupied by the UPF corresponding to the service terminal. The data of physical server resources, the data used to repres...
Embodiment 2
[0147] see figure 2 , figure 2 It is a schematic flowchart of another network failure analysis method disclosed in the embodiment of the present invention. Such as figure 2 As shown, the network failure analysis method may include the following operations:
[0148] 201. Acquire a time-series data set corresponding to a service terminal in a current fault analysis period, the time-series data set includes at least one type of time-series data, and the time-series data included in the time-series data set is used to determine the network status of the service terminal.
[0149] 202. Calculate a year-on-year characteristic value corresponding to each type of time series data in the time series data set.
[0150] 203. Calculate the ring-to-chain eigenvalue corresponding to each type of time series data in the time series data set.
[0151] 204. Calculate the time-series feature value corresponding to this type of time-series data according to the year-on-year feature value ...
Embodiment 3
[0178] see image 3 , image 3 It is a schematic flowchart of a training method for a network fault discrimination model disclosed in an embodiment of the present invention. Such as image 3 As shown, the training method of the network fault discrimination model may include the following operations:
[0179] 301. Obtain multiple training data sets corresponding to service terminals in multiple training analysis cycles, one training analysis cycle corresponds to one training data set, each training data set includes at least one type of training data, and the training data set includes training The data is used to determine the network status of the service terminal.
[0180] 302. For each training data set, calculate a year-on-year feature value corresponding to each type of training data in the training data set.
[0181] 303. For each training data set, calculate the ring ratio feature value corresponding to each type of training data in the training data set.
[0182] ...
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