西北水电Issue(6)：4-14,11.DOI:10.3969/j.issn.1006-2610.2025.06.002
融合信号分解与智能算法的径流集合预报研究
Research on Ensemble Runoff Forecasting Integrating Signal Decomposition and Intelligent Algorithms
摘要
Abstract
Ensemble runoff forecasting plays a crucial role in water resources decision-making and management.The performance of existing forecas-ting systems is constrained by uncertainties in input data,model parameters,and structures,and the forecasting accuracy is closely related to the en-semble size.To address this issue,this study proposes a signal decomposition-based multi-model and multi-parameter ensemble runoff forecasting method by coupling signal decomposition techniques with artificial intelligence forecasting models.The CEEMDAN decomposition technique is used to process non-stationary runoff sequences,and artificial neural networks(ANN)and support vector machines(SVM)are combined for subsequence forecasting.The forecasting sample set is expanded through the random combination of multi-model and multi-parameter forecasting results to form en-semble runoff forecasting results.Validation using the inflow runoff of the Jinping-I Reservoir on the Yalong River shows that the Nash coefficient of the runoff forecasting results by this method can be increased to 0.84,the coverage rate of the ensemble forecasting reaches 55%,and the ensemble size is expanded to the order of 1042,significantly outperforming traditional multi-model methods.This method can accurately extract the characteristic periodic and trend terms of runoff sequences,effectively improve forecasting accuracy,and reduce forecasting uncertainties.It is suit-able for forecasting non-linear and non-stationary hydrological sequences and can provide support for reservoir operation decisions.关键词
集合预报/信号分解/人工神经网络(ANN)/支持向量机(SVM)/不确定性Key words
ensemble forecasting/signal decomposition/artificial neural network(ANN)/support vector machine(SVM)/uncertainty分类
天文与地球科学引用本文复制引用
LI Haichen,WANG Xu,GAO Jie,LIU Mengmeng,ZHAO Zenghai,YI Bo,ZHU Fangliang,GUO Peng,ZHANG Dong,ZHANG Ping..融合信号分解与智能算法的径流集合预报研究[J].西北水电,2025,(6):4-14,11.基金项目
国家自然科学基金项目(U2243232) （U2243232）
国家自然科学基金青年科学基金项目(52309031) （52309031）
中国电力建设股份有限公司核心攻关项目(DJ-HXGG-2024-02) （DJ-HXGG-2024-02）
