人民长江2025，Vol.56Issue(7)：56-65,10.DOI:10.16232/j.cnki.1001-4179.2025.07.008
基于多策略改进合作搜索算法的径流混合预报模型
Hybrid runoff forecasting model based on multi-strategy improved cooperation search algorithm
摘要
Abstract
To address the limitations of low prediction accuracy and poor generalization ability in traditional runoff forecasting methods,this study proposes a hybrid runoff forecasting model integrating Successive Variational Mode Decomposition(SVMD),multi-strategy Improving Cooperation Search Algorithm(ICSA),and spatiotemporal error integrated correction.Firstly,the meth-od decomposes the runoff time series into relatively independent subsequences using SVMD.Secondly,each subsequence is then forecast using Least Squares Support Vector Regression(LSSVR),with its parameters optimized by a CSA enhanced via sinusoid-al initialization,dynamic communication,and random walk mutation strategies,significantly improving global search capability and convergence stability.Finally,the initial forecasts are summed and further refined by spatiotemporal error integrated correction to further reduce residual errors and ensure reliability.Validated in Chitan Reservoir,Fujian Province,China,the model demonstrably outperformed traditional methods(LSTM,ELM,SVR,LSSVR),it achieved higher RMSE,MAE,CC and NSE values values.The NSE values for the forecast period of 1～4 days are 0.986,0.982,0.976 and 0.967 respectively,showing higher accuracy and stability.Validity tests confirmed its capability to accurately capture complex nonlinear runoff relationships and reduce prediction bias,providing a valuable solution for high-precision runoff forecasting under changing conditions.关键词
径流预报/逐次变分模态分解法/合作搜索算法/最小二乘支持向量回归/误差时空综合修正/池潭水库Key words
runoff forecasting/successive variational mode decomposition/cooperation search algorithm/least squares support vector regression/spatiotemporal error integrated correction/Chitan Reservoir分类
天文与地球科学引用本文复制引用
杜成锐,李旻,孙大雁,梁志峰,王金龙,周波..基于多策略改进合作搜索算法的径流混合预报模型[J].人民长江,2025,56(7):56-65,10.基金项目
国家电网有限公司重大科技项目(4000-202355381A-2-3-XG) （4000-202355381A-2-3-XG）
