基于改进PSO的SVM参数优化及其在风速预测中的应用

doi:10.11930/j.issn.1004-9649.2013.11.105.3

中国电力 ›› 2013, Vol. 46 ›› Issue (11): 105-108.DOI: 10.11930/j.issn.1004-9649.2013.11.105.3

基于改进PSO的SVM参数优化及其在风速预测中的应用

祝晓燕, 张金会, 付士鹏, 朱霄珣

华北电力大学机械工程学院,河北保定 071003

收稿日期:2013-07-23 出版日期:2013-11-23 发布日期:2015-12-10
作者简介:祝晓燕（1965—）,女,河北保定人,副教授,从事状态检测与故障诊断研究。

Parameter Optimization of SVM Based on Improved PSO and Its Application in Wind Speed Predictions

ZHU Xiao-yan, ZHANG Jin-hui, FU Shi-peng, ZHU Xiao-xun

School of Mechanical Engineering, North China Electric Power University, Baoding 071003, China

Received:2013-07-23 Online:2013-11-23 Published:2015-12-10

摘要/Abstract

摘要： 针对风电场短期风速预测的准确性问题,提出一种基于改进粒子群优化（PSO）算法的支持向量机（SVM）风速预测方法。通过对基本粒子群算法中的学习因子进行改进,来改善粒子群算法的自我学习能力和社会学习能力,从而使其更有利于收敛到全局最优解,进而能够找到更准确的参数值,使支持向量机的预测误差达到最小,提高风速的预测精度。实验结果表明,与PSO-SVM预测法和SVM预测法相比较,改进PSO-SVM法预测结果更准确。

关键词: 风速预测, 改进粒子群优化（PSO）算法, 支持向量机（SVM）, 参数选择

Abstract: For accurate prediction of short-term wind speeds in a wind farm, a new SVM (support vector machine) predicting method based on improved PSO(particle swarm optimization) is proposed, which is designed to improve the self-learning ability and social learning ability of the particle swarm algorithm by bettering its learning factors, consequently making the PSO more conducive to converge to the global optimal solution and to find a better and more accurate parameter values to minimize the error of support vector machine prediction. The testing results show that compared with the conventional PSO-SVM and SVM prediction, the improved PSO-SVM method is more accurate in prediction result and has lower errors.

Key words: improved PSO, SVM, parameter selection, wind speed forecasting

中图分类号:

TM614

祝晓燕, 张金会, 付士鹏, 朱霄珣. 基于改进PSO的SVM参数优化及其在风速预测中的应用[J]. 中国电力, 2013, 46(11): 105-108.

ZHU Xiao-yan, ZHANG Jin-hui, FU Shi-peng, ZHU Xiao-xun. Parameter Optimization of SVM Based on Improved PSO and Its Application in Wind Speed Predictions[J]. Electric Power, 2013, 46(11): 105-108.

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https://www.electricpower.com.cn/CN/Y2013/V46/I11/105

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基于改进PSO的SVM参数优化及其在风速预测中的应用

Parameter Optimization of SVM Based on Improved PSO and Its Application in Wind Speed Predictions

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基于改进PSO的SVM参数优化及其在风速预测中的应用

Parameter Optimization of SVM Based on Improved PSO and Its Application in Wind Speed Predictions

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