水力发电学报2024，Vol.43Issue(7)：30-40,11.DOI:10.11660/slfdxb.20240703
基于极点对称模态分解的中长期径流预报组合模型
Combined model for medium-and long-term runoff predictions based on Extreme-point Symmetric Mode Decomposition
摘要
Abstract
Extreme-point Symmetric Mode Decomposition(ESMD)is used to predict runoff series based on a runoff forecasting model to solve two problems after runoff series decomposition-large fluctuation ranges of high frequency components and poor forecast accuracy.We use the stationary processing technique of the ESMD to decompose the runoff series,select the best prediction method by analyzing the characteristics of different frequency components,combine Particle Swarm Optimization(PSO)and Least Square Support Vector Machines(LSSVM)for the prediction of high-frequency components,and use the back-propogation(BP)neural network for the prediction of mid-and low-frequency components.A combined ESMD-PSO-LSSVM-BP forecasting model is constructed to forecast annual and monthly runoffs at three hydrological stations in the upper and middle reaches of the Xijiang River.The results show this model,using different forecasting methods for different frequency components,improves the runoff forecasting accuracy significantly.关键词
西江流域/径流预报/非平稳序列/组合预报模型/极点对称模态分解Key words
Xijiang River basin/runoff forecast/non-stationary/combined forecasting models/extreme-point symmetric mode decomposition分类
地球科学引用本文复制引用
李继清,刘洋,张鹏,陈景..基于极点对称模态分解的中长期径流预报组合模型[J].水力发电学报,2024,43(7):30-40,11.基金项目
国家自然科学基金项目(52179014) （52179014）
国家重点研发计划项目(2017YFC0405906) （2017YFC0405906）
