云南水力发电2026，Vol.42Issue(9)：10-14,5.DOI:10.3969/j.issn.1006-3951.2026.09.004
月径流时间序列预测模型研究与应用
Research and Application of Monthly Runoff Time Series Prediction Model
摘要
Abstract
To improve the prediction accuracy of monthly runoff time series,the STL-WPT-SHO/ESOA/COVIDOA-ELM monthly runoff time series prediction model is proposed,and the model is verified by the monthly runoff time series data of Longtan station in Yunnan Province.Firstly,STL is used to decompose the original monthly runoff series into trend term,seasonal term and residual term,and then WPT is used to decompose the residual term into low-frequency and high-frequency parts,a total of four subsequence components are obtained;Secondly,the super parameters of ELM were optimized by SHO,ESOA and COVEDOA;Finally,the STL-WPT-SHO/ESOA/COVIDOA-ELM model is established to predict each component one by one,and the linear set of the predicted values of each component is the final prediction result.At the same time,21 models such as stl-wpt-sho-b are constructed for comparative analysis.关键词
月径流预测/模型/对比分析/验证Key words
monthly runoff forecast/model/comparative analysis/verification分类
建筑与水利引用本文复制引用
董欣林,崔东文..月径流时间序列预测模型研究与应用[J].云南水力发电,2026,42(9):10-14,5.基金项目
国家高分辨率对地观测系统重大科技专项(89-Y50-G31-9001-22) （89-Y50-G31-9001-22）
