基于变压器的光网络报警上下文矢量化表示及其可靠的报警根本原因识别

2021 European Conference on Optical Communication (ECOC) Pub Date : 2021-09-13 DOI:10.1109/ecoc52684.2021.9606141

Jinwei Jia, Danshi Wang, Chunyu Zhang, Huiying Yang, Luyao Guan, Xue Chen, Min Zhang

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引用次数: 5

摘要

提出了一种基于变压器的报警上下文矢量化表示技术，用于报警根本原因识别和相关性分析。识别出3个常见的根告警，准确率为94.47%，并获得了量化关联度的其他相关告警。

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Transformer-based Alarm Context-Vectorization Representation for Reliable Alarm Root Cause Identification in Optical Networks

A Transformer-based alarm context-vectorization representation technique is proposed for alarm root cause identification and correlation analysis. Three common root alarms are identified with an accuracy of 94.47%, and other correlated alarms are obtained with quantified correlation degrees.

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2021 European Conference on Optical Communication (ECOC)

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