Artificial intelligence-based cloud data center fault detection method

摘要

The cloud data center has become the infrastructure for the digital transformation and upgrading of electric power, storing and managing a large amount of key data. This paper designs a deep learning framework based on the gated loop unit to automate the diagnosis of equipment failures in the power cloud data center computer room, and combines timing information to predict the future state based on the past equipment operating state information. It is verified through the data set that the GRU-based deep learning framework proposed in this paper can detect cloud data center failures more accurately than common models such as LSTM, SVM and KNN.