南京信息工程大学学报2026，Vol.18Issue(1)：60-68,9.DOI:10.13878/j.cnki.jnuist.20241217001
融合群分解与Transformer-KAN的短期风速预测
Short-term wind speed prediction by integrating swarm decomposition and Transformer-KAN
摘要
Abstract
Accurate and reliable wind speed prediction is crucial for efficient wind energy utilization.Considering the inherent instability of wind speed,we propose an SWD-Transformer-KAN prediction model that integrates Swarm Decomposition(SWD),Transformer architecture,and Kolmogorov-Arnold Network(KAN).First,the raw wind speed data are decomposed via the SWD method to extract key features.Subsequently,a Transformer-KAN predic-tion model is established for each decomposed subsequence,which fully utilizes Transformer's temporal processing capabilities and KAN's nonlinear approximation strengths.Final wind speed predictions are obtained by aggregating all subsequence forecasts.Experimental comparisons demonstrate that the proposed SWD-Transformer-KAN model exhibits superior predictive performance,achieving a coefficient of determination(R2)of 99.91%.关键词
风速预测/群分解/Transformer/Kol-mogorov-Arnold网络Key words
wind speed prediction/swarm decomposition(SWD)/Transformer/Kolmogorov-Arnold network(KAN)分类
信息技术与安全科学引用本文复制引用
史加荣,张思怡..融合群分解与Transformer-KAN的短期风速预测[J].南京信息工程大学学报,2026,18(1):60-68,9.基金项目
绿色建筑全国重点实验室自主研究课题(LSZZ-Y202414) （LSZZ-Y202414）
陕西省自然科学基金(2021JM-378) （2021JM-378）
