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Title:
CLOUD NETWORK ABNORMALITY DETECTION MODEL TRAINING METHOD BASED ON REINFORCEMENT LEARNING, AND STORAGE MEDIUM
Document Type and Number:
WIPO Patent Application WO/2024/104401
Kind Code:
A1
Abstract:
Embodiments of the present description provide a cloud network abnormality detection model training method based on reinforcement learning, and a storage medium. The method comprises: inputting, into a first detection network of an abnormality detection model, historical time sequence data related to a device to be detected for processing, to generate a first abnormality detection result corresponding to said device at at least one historical moment; determining a detection error corresponding to the first abnormality detection result, and inputting the detection error and at least one piece of historical alarm information of said device into an agent of a second detection network in the abnormality detection model for processing, to generate a second abnormality detection result of said device at a target moment; determining reward information of the second detection network according to the second abnormality detection result and a target abnormality detection result of said device at the target moment; and adjusting network parameters of the agent on the basis of the reward information, to generate a target abnormality detection model.

Inventors:
YANG JIAHAI (CN)
HE XIN (CN)
ZHANG SHIZE (CN)
DONG ENHUAN (CN)
WANG ZHILIANG (CN)
LU JIANYUAN (CN)
LYU BIAO (CN)
ZHU SHUNMIN (CN)
Application Number:
PCT/CN2023/131887
Publication Date:
May 23, 2024
Filing Date:
November 15, 2023
Export Citation:
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Assignee:
HANGZHOU ALICLOUD FEITIAN INFORMATION TECH CO LTD (CN)
International Classes:
H04L41/0604
Foreign References:
CN115514614A2022-12-23
US20210097438A12021-04-01
CN113111996A2021-07-13
CN113743607A2021-12-03
CN114520743A2022-05-20
US20160062815A12016-03-03
US20210256392A12021-08-19
US20210406109A12021-12-30
Attorney, Agent or Firm:
GUANGZHOU ZHUZHI INTELLECTUAL PROPERTY LIMITED (CN)
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