Prediction method of time series data stream based on EMD
基于经验模式分解的时间序列数据流在线预测*

This paper proposed a time series data stream prediction method. By empirical mode decomposition, decomposed the original dataset from re-writable linked window into finite intrinsic mode functions (IMFs) and a residue. Then forecasted each component by maximal Lyapunov exponent method. Finally combined the predicted results of all components into the final value. Experiments with power load show that the combined model has higher precision of prediction and better adaptability compared with other single time series prediction models.