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Model training method, alarm method based on prediction model and related device

A technology of model training and prediction model, applied in the field of information processing, can solve problems such as difficult alarms and large differences in server visits, and achieve the effect of improving accuracy

Active Publication Date: 2020-06-09
BEIJING QIYI CENTURY SCI & TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In practical applications, due to the great difference in the number of visits to the server in different time periods, there are also different requirements for the threshold of the success rate of the login service. It is difficult to meet the above requirements according to the above fixed threshold, so it is difficult to accurately alarm according to actual needs

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  • Model training method, alarm method based on prediction model and related device
  • Model training method, alarm method based on prediction model and related device
  • Model training method, alarm method based on prediction model and related device

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Embodiment Construction

[0065] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiment of the application will be clearly and completely described below in conjunction with the drawings in the embodiment of the application. Obviously, the described embodiment It is only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.

[0066] The model training method and the alarm method based on the predictive model provided in this application can be applied to scenarios with working servers. exist figure 1 In the shown monitoring scenario, the monitoring device 10 is connected to the working server 30 through the network 20 .

[0067] The job server 30 is a server for providing various serv...

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Abstract

A model training method comprises the following steps: determining a training time point sequence based on a plurality of training time points in a first time segment before a time division point andat least two time intervals; selecting monitoring data from all the monitoring data based on the training time point sequence; determining an input weight of a prediction model based on the monitoringdata of each time point in the training time point sequence and the monitoring data of the training time points; determining a test time point sequence based on the test time point in the second timesegment after the time division point and the at least two time intervals; acquiring monitoring data based on the test time point sequence; determining a predicted value at the test time point basedon the monitoring data and the input weight of each time point in the test time point sequence; comparing the predicted value with the monitoring data at the test time point; and if the comparison result meets the model convergence condition, finishing model training. The invention further provides a related device capable of realizing the model training method.

Description

technical field [0001] The present application relates to the field of information processing, in particular to a model training method, an alarm method based on a predictive model, and related devices. Background technique [0002] With the development of network technology, network services provide a lot of convenience for daily life. In order to ensure the reliability of the network service, it is necessary to monitor the server providing the network service. [0003] The existing monitoring method is roughly as follows: a corresponding preset threshold is configured for each type of server data. If it is detected that the relationship between the server data and the preset threshold meets the preset alarm rule, an alarm is issued. For example, the preset threshold for users logging into the service is 99.8%. Alarm when the success rate of user login is below 99.8%. [0004] In practical applications, due to the great difference in the number of visits to the server i...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F11/30G06F11/32
CPCG06F11/3089G06F11/327
Inventor 于敬延
Owner BEIJING QIYI CENTURY SCI & TECH CO LTD