统计与决策2025，Vol.41Issue(4)：35-39,5.DOI:10.13546/j.cnki.tjyjc.2025.04.006
基于组合残差修正的优化神经网络预测方法
Optimized Neural Network Prediction Method Based on Combined Residual Correction
摘要
Abstract
In order to improve the prediction accuracy of single models,this paper proposes an optimized neural network pre-diction method based on combined residual correction.Firstly,the sparrow search algorithm is employed to optimize the parame-ters of neural network to avoid a decrease in prediction accuracy.Secondly,the IOWA operator is introduced to calculate the weighted vector of the neural network model to avoid the fluctuating prediction accuracy of a single prediction model at different time points.Finally,the prediction results of the echo state network model are further corrected.In order to verify the validity of the model,the monthly pork price in Beijing is taken as an example for empirical analysis,and comparison is made with 9 single forecasting models.The results show that the proposed model has higher prediction accuracy than other single prediction models and can accurately predict the prices of other agricultural products with similar characteristics.关键词
IOWA算子/神经网络/麻雀搜索算法/残差修正Key words
IOWA operator/neural network/sparrow search algorithm/residual correction分类
信息技术与安全科学引用本文复制引用
李博,廖梦洁,张健..基于组合残差修正的优化神经网络预测方法[J].统计与决策,2025,41(4):35-39,5.基金项目
北京市博士后工作经费资助项目(2024-zz-062) （2024-zz-062）
扬州大学高层次人才科研启动项目(137013600) （137013600）
