中国电机工程学报2016，Vol.36Issue(23)：6337-6342,6.DOI:10.13334/j.0258-8013.pcsee.152005
基于PSO参数优化的LS-SVM风速预测方法研究
Research on LS-SVM Wind Speed Prediction Method Based on PSO
摘要
Abstract
The impact on LS-SVM prediction model accuracy of the embedding dimension d and time delayτwere studied, which were used as a space reconstruction parameter. And LS-SVM prediction method based on PSO parameter optimization was proposed. In this method, particle swarm algorithm was used to optimize the embedding dimension d, time delay τ and other model parameters (regularization parameterγ, kernel function parameterσ), and then established prediction model. 2 groups of wind speed were predicted by using this method. The prediction error is about 5.79% and 7.33%, and the error of the contrast method (optimizeγ,σonly) is 8.22% and 11.10%. The results show that the optimal selection of d, τ, γ, σ is necessary. Compare with the comparison model, this method can greatly improve the prediction accuracy.关键词
风速预测/最小二乘支持向量机/粒子群算法/参数优化/空间重构Key words
wind speed prediction/LS-SVM/PSO/parameter optimization/space reconstruction分类
信息技术与安全科学引用本文复制引用
朱霄珣,韩中合..基于PSO参数优化的LS-SVM风速预测方法研究[J].中国电机工程学报,2016,36(23):6337-6342,6.基金项目
中央高校科研业务费项目(2015MS102)。Supported by the Fundamental Research Funds for the Central Universities (2015MS102) （2015MS102）
