The introduction of 5G technology further increases the complexity of the network,therefore,operators need to develop new strategies to ensure network quality and maintain competitiveness.However,with the expansion of network scale,the operation and maintenance of cellular networks have become more difficult.Traditional network fault diagnosis methods rely too much on manpower and professional knowledge,resulting in low diagnostic efficiency and unsatisfactory results.Therefore,there is an urgent need to adopt intelligent and efficient network fault diagnosis methods to address these challenges.The article proposes a cellular network fault diagnosis method based on graph convolutional neural networks,hoping to be helpful for the research of 5G network fault diagnosis.
维普
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