江汉大学学报（自然科学版）2024，Vol.52Issue(4)：27-36,10.DOI:10.16389/j.cnki.cn42-1737/n.2024.04.003
基于季节波动序列的PSO-FNSGM(1,1,k)模型及其应用
PSO-FNSGM(1,1,k)Model Based on Seasonal Fluctuation Sequence and Its Application
摘要
Abstract
For the complex sequence with the characteristics of annual fluctuation and sea-sonal fluctuation,a grey prediction model based on seasonal factors,particle swarm optimi-zation(PSO),and Fourier optimization was used in this paper to achieve accurate prediction of seasonal fluctuation series.Firstly,this prediction model proposed three seasonal factors by changing the annual effect coefficient and then compared these factors.Secondly,to re-duce the interference of time variation on the sequence,this paper added linear correction terms to the prediction model and used the PSO algorithm to find the optimal parameters to improve the prediction accuracy of the model.Finally,by considering the influence of season-al variation on the sequence,the Fourier series was used to fit the residual series of the mod-el.In this paper,the model was applied to the simulation and prediction of the net hydroelec-tric power generation in China,and the final error was 1.22% .The research shows that the model has higher prediction accuracy for fluctuation sequences.关键词
季节因子/周期序列/灰色模型/粒子群优化算法/傅里叶级数Key words
seasonal factor/periodic sequence/grey model/particle swarm optimization/Fourier series分类
信息技术与安全科学引用本文复制引用
张怡萱,胡坰煌,李钒,熊昕,胡曦..基于季节波动序列的PSO-FNSGM(1,1,k)模型及其应用[J].江汉大学学报（自然科学版）,2024,52(4):27-36,10.基金项目
国家自然科学基金资助项目(61901298) （61901298）
江汉大学省部共建精细爆破国家重点实验室自主研究课题项目资助(PBSKL2022303) （PBSKL2022303）
江汉大学省级大学生创新训练项目(2022zd106) （2022zd106）
江汉大学校级科研项目(2021yb057) （2021yb057）
湖北省教育厅科学研究计划指导性项目(B2022280) （B2022280）
