Renmin Zhujiang (Jan 2021)
Application of Improved EEMD-NNBR Coupling Model in Annual Runoff Prediction
Abstract
The ensemble empirical mode decomposition (EEMD) technique is improved by the extremum center cubic spline interpolation. On this basis, the improved EEMD is combined with the nearest neighbor bootstrapping regressive model (NNBR) to obtain an improved EEMD-NNBR coupling model. The improved EEMD can better fit the upper and lower extreme points, and extend the sequence mean to the two ends of the sequence to reduce the end effect. This paper firstly decomposes the annual runoff series by the improved EEMD to obtain the intrinsic mode function (IMF) and trend term, and then establishes the NNBR for each IMF and trend term to obtain the predicted values of decomposed series, and accumulates the predicted values to get the annual runoff, finally applies the improved EEMD-NNBR coupling model for the annual runoff prediction of Pingshan Station. The results show that compared with the original coupling model, the mean relative error of the improved EEMD-NNBR coupling model have reduced from 10.08% to 8.59%, so the proposed model can improve the accuracy of runoff prediction.
