Data center KPI prediction based on wavelet neural network - Yao Ronghuan (Dianzi Jishu Yingyong, 2019)
Time series prediction is an important part of abnormal detection of key performance indicators in data centers. For the time series, the wavelet basis function is used as the implicit layer node transfer function to construct the wavelet neural network for prediction. At the same time, the momentum gradient descent method is adopted to improve the learning efficiency of the neural network. Then the optimal solution is trained according to the particle swarm algorithm as the initial neural network parameters. The value is finally simulated using MATLAB, and the time series of key performance indicators are predicted with higher accuracy.